Tag: ai

  • Google’s Bard Vs. ChatGPT: Who Wins the AI Battle?

    On November 30, 2022, a company in San Francisco, USA, debuted its most ambitious AI project that is ChatGPT. And within five days of its launch, ChatGPT got 1 million users worldwide. This feat is what Silicon Valley products like Facebook or Instagram could achieve in the past, as even Instagram took 2.5 months to get a 1Million user base.

    ChatGPT, developed by OpenAI, became a massive hit and seems like an overnight success. But the research and development powering the GPT model that powers it took decades, going back to the 1980s when people in the field of Artificial Intelligence started working on recurrent neural networks (RNNs) – a sort of AI that can process sequential data such as text and human speech. The breakthrough came in 2017 when some scientists working at Google Brain came up with the Transformer Architecture, which became the basis of OpenAI’s GPT (Generative Pre-Trained Transformer) after GPT-1, GPT-2, GPT-3, we got ChatGPT Chatbot, a generative AI chatbot capable of understanding dialogues and generating creative text content when prompted, poems, speeches, and letters even.

    On the other hand, Google, the company with the hegemony in web search over the past two decades, has been actively working on AI since the early 2000s with its Google Brain project and has since made several notable achievements and breakthroughs in the field of AI. As a prominent player in AI, Google has developed numerous AI-driven products and services, which include Google Translate, Google Autocomplete, Google Voice, Google Photos, Google Cloud Natural Language API, Google Cloud Speech API, and the AI chatbot Bard. Beyond this, Google also leads cutting-edge AI research and development and publishes several papers in top AI conferences and journals.

    In 2016, a few months after becoming CEO of Google, Sundar Pichai made a sweeping proclamation that Google, whose name had become synonymous with search, would now be an “AI-first” company. After taking the company reins, Mr. Pichai’s announcement was his first order of business at Google’s annual I/O developers’ meet, but believe it or not, Google is not an ‘AI-first’ company at present, and it is playing to catch up with OpenAI, and Microsoft Inc.

    On February 6, just a day before Microsoft announced its new Bing Chatbot powered by OpenAI’s ChatGPT, Google’s CEO, in a blog post, announced Bard, an experimental conversational AI service powered by LaMDA (Language Model for Dialogue Applications). The announcement of Bard appeared to be a pretty rushed one. And a factual error about James Webb Space Telescope (JWST) discovering exoplanets (It was the European Southern Observatory’s large telescope that took the first pictures of exoplanets in 2004 and not JWST) in a promotional video for Bard made Google’s parent company Alphabet lose $100 billion (9%) in market value.

    So, even though Google has been working on its AI and deep learning developments for quite some time now, it has to cover a lot of ground for generative AI and this AI battle. With so many companies like Microsoft, IBM, Apple, etc., investing heavily in AI and ML research and development, Google certainly has a lot of competitors, and Microsoft’s Bing AI is leading from the first when it comes to challenging Google’s Search Platform.

    ChatGPT vs Bard AI – Key Highlights
    GPT-3.5 and GPT-4 – The Large Language Model Powering ChatGPT and ChatGPT Plus
    LaMDA – Google’s Language Powering Bard
    Which AI Chatbot is Better – ChatGPT or Google’s Bard?

    ChatGPT vs Bard AI – Key Highlights

    ChatGPT was created by OpenAI— using a specially tweaked version of OpenAI’s Generative Pre-training Transformer 3 (GPT-3) or GPT-4 (depending on the version)— and Bard AI was created by Google. It was announced in February 2023, just a day before Microsoft announced its new Bing Chatbot powered by OpenAI’s ChatGPT, while ChatGPT was launched in late November 2022. Bard AI uses Google’s Language Model for Dialogue Applications (LaMDA).

    If we talk about data sources, ChatGPT has trained on a massive dataset of text, including Wikipedia, books, documents, articles, and content taken from the open internet. However, its sources end in 2021, limiting the latest world events and research. And Bard AI trained on Infiniset, a blend of data (set) including Common Crawl, Wikipedia, documents, and conversations and dialogues from the web. Google claims that Bard will search the web in real-time to find the most recent answers to questions and the latest research. Bard combines the breadth of the world’s knowledge with the power, intelligence, and creativity of Google’s large language models.

    ChatGPT is open for free to all users, ChatGPT Plus, the newer, upgraded version of ChatGPT, based on the GPT-4 model, is available for use at a $20/month subscription to include access to more capabilities, access during peak times, longer content, visual inputs, faster response times, and priority access to new features. Google’s Bard AI is free to use, but the access is not publicly available. However, you can join the waitlist, and soon access will be provided.

    Now coming to knowledge and accuracy, ChatGPT is ignorant of events after 2021 due to its training data cut-off. But the Bard AI can search the internet for current information and use that to generate responses. However, Bard AI can also make hard-to-spot errors, including the error mentioned below.

    When asked about Google’s AI efforts and progress, the company claimed that it launched the GPT-2 and GPT-3 models, which isn’t the case— OpenAI developed and launched them.

    GPT-3.5 and GPT-4 – The Large Language Model Powering ChatGPT and ChatGPT Plus

    The AI chatbot of ChatGPT works by using natural language processing (NLP) and machine learning algorithms to understand and generate human-like responses when prompted by users. It is based on OpenAI’s Generative Pre-training Transformer’s third version (GPT-3) and uses an extensive neural network trained on a massive dataset of text and codes.

    When a user inputs a prompt or query, ChatGPT processes the input using its NLP algorithms to understand the meaning and intent behind the user’s message. It then uses its machine learning algorithms to generate a response based on its training data and the context of the conversation. The response is thus shown to the user in natural language.

    GPT-4 vs GPT 3.5: 5 Key Differences Explained
    OpenAI claims its new upgraded version GPT-4 is much more capable than GPT-3.5. Let’s see the 5 key differences between the GPT-4 and its predecessor in this article.

    GPT-3, the powerful and advanced language model with 175 billion parameters, can generate coherent and contextually appropriate language. GPT-3.5 is an update to GPT-3 that includes new capabilities and improved performance, and GPT-4 is expected to have an even larger vocabulary size and more advanced deep-learning concepts. GPT-4 is capable of analyzing visual inputs and logical interpretation of images. It also accepts up to 25000-word for better context and creates longer, creative content than ChatGPT.

    LaMDA – Google’s Language Powering Bard

    It was the annual Google I/O event in 2021 that Google announced LaMDA (Language Model for Dialogue Applications). It is an advanced AI language model developed to engage in free-flowing conversations across endless topics and can mimic human dialogue. During its training, LaMDA picked up on several nuances of open-ended conversation to ensure sensible and impressive replies. It can prioritize helpful suggestions and witty retorts, avoiding generic responses such as “Okay” or “I’m not sure.”

    To guarantee factual accuracy, Google integrated LaMDA with third-party information sources to source facts and avoid generating conflicting or false information— as concerns were raised over the misinformation generated by existing chatbots.

    LaMDA is powered by Google’s Transformer (deep learning) architecture (developed in 2017), which enables the model to “read” multiple words at once and analyze their relationships with one another. Even OpenAI’s GPT models rely on the same Transformer architecture.

    Which AI Chatbot is Better – ChatGPT or Google’s Bard?

    ChatGPT is the most successful AI chatbot at the moment. It took just five days since its launch on November 30, 2022, to get 100m users, and by January, it had 100m users worldwide. While it is too early to conclude which AI Chatbot— ChatGPT or Google’s Bard— is the better one and who wins the AI battle, it is worth commenting that Bard is still an experiment as claimed by Google and makes factual errors like the one mentioned above. And ChatGPT is limited by its training data set that remains anchored to the past, 2021.

    That being said, ChatGPT is now upgraded to the newer version, ChatGPT Plus, and it is much more advantageous when it comes to generating creative content, writing codes, or doing some research work.

    It is also worth mentioning that the use of these two AI Chatbots depends upon user needs and how one uses these tools, though a careful approach and fact-checking of some facts, once in a while, is certainly needed.

    FAQs

    What are the major differences between Google’s Bard and ChatGPT?

    • ChatGPT was created by OpenAI, whereas Bard AI was created by Google
    • ChatGPT’s data sources end in 2021, however, Bard claims that it searches in real-time
    • ChatGPT’s knowledge and accuracy are till 2021 due to its training data cut-off. But the Bard AI can search the internet for current information and use that to generate responses

    What are the language models in which ChatGPT and Google’s Bard work?

    The AI chatbot of ChatGPT works by using natural language processing (NLP) and machine learning algorithms to understand and generate human-like responses when prompted by users.

    While Google’s Bard works by using LaMDA (Language Model for Dialogue Applications).

  • 6sense: One-Stop Solution for Revenue Generation

    Company Profile is an initiative by StartupTalky to publish verified information on different startups and organizations. The content in this post has been approved by 6sense.

    Both sales and marketing are significant pillars of every business as they act as a catalyst for generating revenue. While marketing involves building brand awareness among audiences, sales turn that viewership into profits by converting leads into actual customers.

    However, the marketing and sales team needs to understand consumer behavior through appropriate data and visibility. It is when 6sense comes into the picture. This company helps the revenue team to access relevant statistics with the help of advanced technology.

    In this article, know about 6sense, its business, founders, products, startup story, funding, and more.

    6sense – Company Highlights

    Company Name 6sense
    Headquarters San Francisco, California, United States
    Primary Industry SalesTech
    Founders Amanda Kahlow, Dustin Chang, Premal Shah, Shane Moriah, and Viral Bajaria
    Founded In 2013
    Website 6sense.com

    6sense – About
    6sense – Founders and Team
    6sense – Startup Story
    6sense – Mission and Vision
    6sense – Products and Services
    6sense – Business Model
    6sense – Funding and Investors
    6sense – Partners
    6sense – Merger and Acquisitions
    6sense – Growth
    6sense – Awards and Achievements
    6sense – Competitors

    6sense – About

    6sense is a San Francisco-based company that reinvents the way B2B organizations create, manage, and convert their pipeline to revenue. Its revenue AI eliminates guesswork and arms the organization’s revenue team with important data and visibility that is required to create and convert high-quality pipelines into revenue.

    Currently, Jason Zintak is the CEO and Viral Bajraj is the CTO of 6sense. The company is growing at a faster pace with 6 branches in the United States, the United Kingdom, and India. Moreover, it is ranked the 130 fastest-growing companies in North America on the Deloitte Technology Fast 500TM.

    6sense – Founders and Team

    6sense, Founders - Amanda Kahlow, Dustin Chang, Premal Shah, Shane Moriah, and Viral Bajaria
    6sense, Founders – Amanda Kahlow, Dustin Chang, Premal Shah, Shane Moriah, and Viral Bajaria

    Set up in 2013, 6sense was founded by Amanda Kahlow, Dustin Chang, Premal Shah, Shane Moriah, and Viral Bajaria.

    Amanda Kahlow

    Amanda Kahlov is a graduate of the University of Colorado Boulder and is the founder and ex-CEO of 6sense. Moreover, she founded CI Insight Inc. and held the role of CEO. Presently, she is working as the director at MAHA global and an advisor at Brit + Co.

    Dustin Chang

    Co-founder of 6sense, Dustin Change has graduated from the University of Washington. He has co-founded Grepdata and is working as CTO of Stealth Startup.

    Premal Shah

    Earned a degree in Computer Science from the University of Southern California, Premal Shah is co-founder of 6sense. Moreover, he has also co-founded GrepData and worked in Livingly Media for almost 7 years.

    Shane Moriah

    Co-founder of 6sense, Shane Moriah has graduated from Stanford University and has a degree in BS, Computer Science. He has co-founded 6sense and GrepData and is now, working as Chief Technology Officer in Settle.

    Viral Bajaria

    Viral Bajaria graduated from the University of Southern California with a degree in Computer Science before co-founding and working as CEO of 6sense.

    Talking about the company size, currently, it employs 1200 employees, ranging from data scientists and business leaders to engineers and mathematicians.

    6sense – Startup Story

    6sense was developed by Amanda Kahlow along with other co-founders in 2013 after consultation with Cisco- the technology company. It was launched as a tool for organizations running marketing and sales businesses by predicting the inclination of potential customers.

    In 2014, the company launched the world’s first B2B sales and marketing prediction intelligence platform. It achieved another milestone by receiving a patent for a machine learning method to predict the future of B2B sales and marketing in 2016.

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    Since then, there is no stopping as 6sense has been recognized as the leader by several renowned organizations.

    6sense – Mission and Vision

    The common goal of 6sense is to change B2B sales and marketing with predictive intelligence. It focuses on offering the best solutions to help marketers and sellers succeed.

    6sense – Products and Services

    The core platform comprises foundational features that the sales and marketing team needs for scaling their ABM programs. The solutions offered by the company are:

    • Account Identification
    • Data Enrichment and Management
    • Intent Data
    • Audience Building
    • Advertising
    • Predictive Analysis
    • Orchestration and Workflows
    • Pipeline Intelligence
    • Conversational E-mail
    • Sales Intelligence

    6sense – Business Model

    The account engagement platform of 6sense helps B2B organizations achieve predictable revenue growth by providing the access to AI, big data, and machine learning to every member of the revenue team. The company’s Revenue AI platform uncovers anonymous buying behavior, predicts the right accounts to target at the right time, and enables the sales and marketing team to engage buyers with multi-channel and multi-touch campaigns.

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    Its business model revolves around helping revenue teams know every necessary detail about their buyers so that they can generate more opportunities, increase deal size, and win over the competition.

    6sense – Funding and Investors

    6sense raised total funding of $426 million over 8 rounds. On 20 January 2020, the latest funding round was held and the company received $200 million in Series E Round. It is funded by 19 investors and some of these are SoftBank Vision Fund, B Capital Group, Harmony Partners, Industry Ventures, Venrock, Insight Partners, and Blue Owl.

    Date Round Number of Investors Money Raised Lead Investor
    January 20, 2020 Series E 10 $200 million Blue Owl, MSD Partners
    March 30, 2021 Series D 4 $125 million D1 Capital Partners
    January 15, 2020 Series C 1 $40 million Insight Partners
    April 16, 2019 Venture Round 6 $27 million Industry Ventures
    February 1, 2019 Seed Round 1
    July 1, 2015 Series B 1 $2 million Salesforce Ventures
    February 19, 2015 Series B 3 $20 million Bain Capital Ventures
    May 20, 2014 Series A 4 $12 million Battery Ventures, Venrock

    6sense – Partners

    6sense believes in partnering with renowned firms to expand its horizons. It has collaborated with around 24 partners and some of these are:

    • Chatfunnels
    • Drift
    • Mediafy
    • Hero Digital
    • Ignitim
    • ROI-DNA
    • Adobe Target
    • Bombora
    • Hushly
    • Reactful

    6sense – Merger and Acquisitions

    Over years, the company has acquired a total of 4 companies. The list of companies acquired is:

    Company Year of Acquisition
    Granite Media Group Inc. 2022
    Slintel 2021
    Fortella 2021
    ZenIQ 2018

    6sense – Growth

    The estimated annual revenue of 6sense in 2022 is $245 million per year. And its current valuation stands at $5.2 billion (January 2022). In addition, the employee count has increased by 127% and the monthly rank growth of the website is 13.63%.

    6Sense in 6 Minutes

    6sense – Awards and Achievements

    6sense, the global platform is rewarded with several awards and achievements. It closed out 2022 with some of these awards and achievements:

    • Best Workplaces for Women
    • Best Company for Diversity
    • Best Company Culture
    • Best CEO
    • Best Company Compensation
    • Best Company Outlook
    • Recognized as a Leader in the December 2022 Gartner Magic Quadrant for ABM Platforms
    • Tech Cares Award by TrustRadius

    6sense – Competitors

    With 6sense offering solutions across different parts of the world, it faces cut-throat competition worldwide. Some of its competitors are:

    • Demandbase
    • ZoomInfo
    • HubSpot
    • Terminus
    • RollWorks
    • Marketo
    • Clearbit
    • Radius

    FAQs

    What is 6sense and how does it help sales teams?

    6sense is an AI-driven revenue intelligence platform that helps sales and marketing teams to identify and engage with high-value accounts more effectively.

    How does 6sense use AI and machine learning to improve revenue generation?

    6sense uses AI and machine learning to identify buying intent signals, providing real-time insights to sales teams for more effective engagement and improved revenue generation.

    What kind of businesses and industries can benefit from using 6sense?

    B2B businesses with longer sales cycles, high-value products/services, and complex sales teams can benefit from using 6sense’s revenue intelligence platform.

  • How is AI Transforming HR for Companies?

    Human resources are no less than a building block for organizations. A robust HR team can take companies and organizations to the next level; at the same time, a weak one can spoil established companies. It is vital to nurture and improve the human resources department. After all, this service line recruits the workforce. Stats show the AI market is expanding at a CAGR of 38.1% between 2022 to 2030. AI is claimed to be a top priority in their business plans by 83% of companies.

    Artificial intelligence is transforming HR by making it more efficient and unbiased. Contrary to what many people assume, AI has the power to enhance the concept of human contact in HR.

    Human resources deal with people and their attitudes. From planning to implementation, several processes come under the HR department. Making new policies, ensuring onboarding standards meet the standards, and whatnot— the HR service line also looks into labour relations, performance management, and job design. The HR team assists in achieving the mission and vision of an organization. The use of AI in HR will not only increase the efficiency of the company but also give employees more alignment with its objectives.

    Impacts on Jobs Due to AI in 2022 Worldwide
    Impacts on Jobs Due to AI in 2022 Worldwide

    As of 2022, the global AI market is valued at over $136 billion. Over the next 8 years, it is expected to increase by over 13 times. AI has and will have a heavy impact on job opportunities. It is estimated 2.3 million jobs will be created, while 1.8 million jobs will be eliminated by AI worldwide in 2022.

    What is Artificial Intelligence?
    How is AI Influencing Human Resources?
    Companies using AI for HR Management

    What is Artificial Intelligence?

    AI refers to Artificial Intelligence, a tech which enables computers to think and acts like a human. Organizations are using AI to improve productivity. AI takes decisions based on the input provided. It uses a certain kind of algorithm. With work-from-home culture now mainstream and organizations becoming people-sensitive, the need for AI is escalating.

    Most of the activities executed by HR are now being managed by AI. It empowers human resources to enhance contacts. According to a survey, 60% of organizations are using AI for talent management.

    Key Benefits of Artificial Intelligence
    Key Benefits of Artificial Intelligence

    How Artificial Intelligence Is Transforming Business
    The mimicry of human intelligence is called Artificial Intelligence. Or Thedevelopment of intelligent machines, thinking, and working like humans is called Artificial Intelligence. With the help of machine learning, we can develop an Artificial Intelligence. Machine Learning is an application of …


    How is AI Influencing Human Resources?

    Uses of AI to Assist Workers in Their Organization as of 2020
    Uses of AI to Assist Workers in Their Organization as of 2020

    Artificial Intelligence in Daily Tasks

    AI can take over several tasks that the human resources department deals with on a day-to-day basis. It can give responses to prospective and current employees. It can also help with questions related to policies and procedures. And this is just the tip of the iceberg when it comes to AI’s capabilities. It can also free up time for HR professionals to focus on other work.

    Handling forms of different kinds, simplifying training sessions, and AI systems can execute various other tasks.

    For organisations, choosing the right talent is a crucial task since employees are the cornerstone to success. When it comes to skills, companies generally have some set of standards. AI can help the HR department to filter resumes as per the desired skill set. AI systems can screen resumes according to the data they are trained on. The department will then have to spend lesser time on the selection process.

    Providing Training

    AI can help new employees by providing efficient training. A conversational chatbot can be used for this purpose. Employees facing any difficulty can send messages to the chatbot. The latter will reply based on the way it’s programmed. Moreover, the chatbot shall give employees the flexibility to complete external and internal training according to their convenience. At times, employees don’t know whom to contact for queries. An AI-powered helpdesk can facilitate the situation.

    AI in decision Making

    Artificial Intelligence can help employees to understand their moods better. Due to workload, employees aren’t able to give their best at times. AI can be trained to provide personality and behaviour insights. Individuals can then use this system to facilitate decision-making.

    Employee Retention

    AI can help the HR team to analyze the reasons behind layoffs and retain more employees. Believe it or not, AI-based systems can help manage the workforce, and that too a satisfied one.

    AI can detect and analyze employees who are disengaged or unproductive. It can provide insights as to where the company is lacking, or why its people are discontent.


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    Appraisals

    Appraisals keep the workforce motivated. And the process should not be partial or biased. AI has a role to play here as well. It can ensure employees get the results in tandem with their performance. Giving appraisals or bonuses to the suitable candidate can boost productivity immensely. Moreover, appraisals require neutral thinking, something which AI is capable of.

    Companies using AI for HR Management

    Companies such as Google, Amazon, IBM, Unilever, L’Oréal, IKEA, Adecco, Hays, Deloitte, Vodafone, PwC, Oracle, TCS, Accenture, and Tech Mahindra have adopted AI for HR Management.

    Some AI platforms/tools for HR selection and recruiting are HireVue, Mya Systems, HiredScore, Wade & Wendy, AllyO, Textio, Turing, Toptal, Manatal, Skillate, TurboHire, Talenture, Fetcher, SeekOut, Zoho Recruit, Paradox, Humanly, Findem, hireEZ, AmazingHiring, Loxo, Eightfold.ai , Textio, myInterview, and Arya, Pymetrics.

    AI cuts time spent on CV verification, and other recruitment processes. The best eligible candidates are filtered out. Unilever, L’Oréal, and IKEA are the B2C using AI to transform their Candidate Sourcing Strategies.

    Company Name AI Hiring Assistant/solution Purpose
    IKEA Robot Vera Conduct interviews and send out
    customized follow-emails
    Unilever HireVue Assessments Hire the best and most diverse graduates
    among potential candidates
    L’Oréal Mya Filter out the best candidates among the
    received job applications

    AI adoption in HR is increasing. Here is a list of a few companies revolutionizing recruiting process using AI.

    AI platform/solution used Companies using the platform
    HireVue 700+ companies, including Unilever, Vodafone, PwC, and Oracle
    Mya Systems L’Oréal, Adecco, Hays, Deloitte, and more
    HiredScore Trusted by 40% of the Fortune 100: Intel, Dell, Domino,
    Johnson & Johnson, and more
    Wade & Wendy E-Trade, Randstad, Comcast, and more
    hireEZ Deloitte, VISA, Amtec, Wayfair, CommonSpirit, and more
    AllyO Walmart, Hilton, AT&T, FedEx, Arbys, and more


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    Conclusion

    The impact of AI on HR Management is now extending to use cases and problems hitherto unexplored. It is providing helping hands to people in their work. Health, finance, banking, computing, marketing, and management. Artificial Intelligence is penetrating every imaginable industry. With unbiased results and the ability to be improved further, AI is here to stay.

    FAQs

    How will artificial intelligence affect human resources?

    AI provides HR departments with an opportunity to improve the candidate and employee experience by automating repetitive, low-value tasks and freeing up time to focus on the more strategic, creative work that HR teams need and want to get done.

    What is artificial intelligence in human resources?

    At a high level, AI is a technology that allows computers to learn from and make or recommend actions based on previously collected data. In terms of human resources management, artificial intelligence can be applied in many different ways to streamline processes and improve efficiency.

    What is human resource transformation?

    Human resource transformation is the process of fundamentally rethinking and rechartering the HR function/department in the organization. If HR professionals do that, they become the “go-to” people to help operating managers address “people problems” they face in getting the organization’s work done.

    Can technology replace human resources?

    No, technology is not stealing human resources jobs; instead, it’s helping small businesses work more efficiently. Although apps and software eliminate some tasks, they typically aren’t enough to replace a person in the workplace.

    What are some benefits of AI?

    • 24×7 Availability
    • Saves time
    • Saves money
    • Reduces Human Errors
    • Removes human bias
    • Daily Applications
  • How is AI Being Used in Fashion Industry?

    The fashion industry is no more about just making and selling clothes. Anybody who thinks they’ll set up a good-looking website, put tons of choices, and hope that customers will follow is living in La La Land.

    It doesn’t work like that anymore. The fashion industry is leveraging the latest advancements in technology to boost sales and clientele. Social media is flooded with DIYs, small fashion brands, and fashion giants so it’s safe to say that the market is booming with options for customers.

    Projected Revenue of the Indian Fashion Industry from 2017 to 2027
    Projected Revenue of the Indian Fashion Industry from 2017 to 2027

    Brands are shifting towards AI to make their voice heard and stand out from the clutter. AI will be an inseparable part of our life. Predictions show Revenue of the Indian Fashion Industry will grow 16.32% annually (CAGR 2022-2027) to reach $39.42 billion by 2027. From automated messages to attention-grabbing notifications, from suggesting sizes to customers to building preferences, fashion brands all over the world are using AI to their benefit.

    Demand and Supply Projection
    Automated Clothes Sorting
    Inventory checks and Re-stocking
    Designing Clothes
    Personalized Recommendations

    Here’s how AI is being used in the Fashion Industry:

    Demand and Supply Projection

    Brands like H&M are sitting on huge amounts of unsold clothing that will lead to lost money. This happens because nowadays brands focus on producing bulk clothing as per the latest trends which go out of fashion swiftly, making room for new trends and thus, production of more new clothes. This costs brands a lot of money and also contributes to wastage.

    Brands are now using AI to predict sales according to trends, product type, color, price, and range factors. This is helping brands minimize the extra product and generate increased revenue as there is less money wastage. Returns are also reduced due to smart prediction of demands.

    Automated Clothes Sorting

    AI Robots used for Sorting Clothes
    AI Robots used for Sorting Clothes

    Sorting and arranging clothes can be a difficult task as it requires labor and time. Most warehouses have people doing it for you and they cannot work 24/7. It is also costly and ineffective. Therefore, big brands like GAP are testing AI to sort clothing for you according to size, color, or preferences that can be just put into a box and shipped to your house via a drone. Through deep learning, the robot can be trained to handle fragile items like sunglasses more gently than jeans.


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    Inventory checks and Re-stocking

    Malls and stores are being monitored by a camera that tracks the product that is out of stock. They can automatically inform the manufacturer about the shortage. To make it even more efficient, the functioning is such built that they scan data to confirm whether the same product is lying in some other store and being sold so that it can be brought to another store. This reduces wasteful manufacturing and saves money.

    Designing Clothes

    Use of AI for Designing Clothes
    Use of AI for Designing Clothes

    Yes, you read that right. Your clothes might be designed by a robot rather than a human. Popular online fashion retailers like Amazon and Myntra are using AI to generate designs for clothes.

    One of the brands on Myntra, Moda Rapido, sells clothes designed by robots. They take inspiration from data about customer preferences and social media trends. Fascinating right? We thought we are far from robots and here they are designing clothes for us.


    How Artificial Intelligence Is Transforming Business
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    Personalized Recommendations

    Myntra using AI for Clothes Recommendation
    Myntra using AI for Clothes Recommendation

    AI is making the lives of fashion retailers easy by providing them with sorted data as per the likes of the customers. Earlier, we would see the clothes and find out what works for us but now, we get recommendations of clothes that we might like. This is done by AI by carefully analyzing previous orders and finding out color, style, and size preferences.

    Conclusion

    AI is changing the future of the fashion industry for the better. It is proven to be more sustainable, cost-effective, and user-friendly. But they will also cost many employees their jobs, not only in the lower posts but also as designers. Let’s see if robots can be great designers. For now, it can be concluded that we are much closer to the age of robots than we’d like to think.

    FAQs

    How AI is used in the fashion industry?

    AI is used in the fashion industry to help improve the efficiency of manufacturing processes. AI systems are also used to spot defects in the fabric.

    Which industries use AI the most?

    Healthcare, Education, and Marketing are the sectors that employ AI the most.

    Can AI design clothes?

    Fashion designers are increasingly using artificial intelligence to design clothes as a tool for innovation.

    How can Machine Learning be used in fashion?

    Machine Learning uses existing fashion trends and customer data to produce a model to fit the market need. It boosts the design process.

    What fashion brands use Artificial Intelligence?

    • Nike
    • Zara
    • Dior
    • H&M
    • Macy’s
    • Nordstrom
  • Is AI Going to Take Over the Creative Jobs Too?

    Artificial Intelligence or AI is the ability of machines to perform certain tasks that typically require human intelligence. It allows the machines to understand and achieve specific goals. Simplistically, machines learn, automatically, from existing data without being assisted by human beings.

    When machines are able to absorb huge amounts of unstructured data such as text, images and audio, it is called deep learning. There are four types of Artificial Intelligence –

    • Reactive Machines
    • Limited Memory
    • Theory of Mind
    • Self- Awareness

    Human beings, today, are surrounded by examples of Artificial Intelligence and that way it has permeated our day-to-day existence.

    • Siri, Alexa and other smart assistants
    • Self-driving cars
    • Robo-advisors
    • Conversational bots
    • Smart Email Apps
    • Search and Recommend Algorithms
    • E-Payments
    • OTT recommendations
    • Social Media
    • Music Streaming Services
    • Google Maps and Navigation
    • Text Editors and Autocorrect

    Future Uses of AI
    AI vs. Human Creativity – Can AI Take Over Creative Jobs?

    Future Uses of AI

    AI is advancing at a break-neck speed, similar to the exponential growth witnessed by database technology in the late twentieth century. The importance of data has been amplified by AI’s large appetite to store, retain and analyse data.

    ‘Metaverse’ was a term that was first heard in the 1992 science fiction novel ‘Snow Crash’. At that time, it was considered too futuristic and a concept of science fiction. Yet, less than 30 years later, it is on the verge of becoming a reality.

    The metaverse is a single, universal and immersive virtual world.  In simple words, it is an alternate universe facilitated by virtual reality and augmented reality.

    There are existing uses of a metaverse in the gaming industry.  This could very well leap into the everyday world.  Be it conferences, meetings, weddings or parties, the metaverse can host it all.  The possibilities of its uses are endless.

    AI vs. Human Creativity – Can AI Take Over Creative Jobs?

    Human beings are trying to achieve a system that emulates our intelligence. Achieving this requires a starting point. What is that starting point? A massive amount of data.

    If we want a computer to tell us the difference between a tiger and a lion, we have to first feed it with thousands of images of tigers and lions. However, human intelligence is a multi-faceted tool.  

    A tool with the ability to make decisions, create, learn, evolve, draw inspiration from a lifetime of experiences, feel, empathize, think differently and, essentially, be a square peg in a round hole.

    “Our intelligence is what makes us human, and AI is an extension of that quality.”
    ― Yann LeCun

    Creativity

    Albert Einstein says  – “Creativity is seeing what everyone else saw, and thinking what no one else thought”.

    The best example of this is probably, the advertising industry.  This industry has, possibly, made the best use of AI. It has created award-winning campaigns. ‘The Next Rembrandt’ is a perfect example of how AI can be utilized optimally to understand the Dutch Master’s painting style, his use of colour, lights, his subject interest, etc. All this data can then be used to produce a modern painting emulating his style.

    Yet, machines can never know, if Rembrandt himself would have evolved or if he might have shifted his interest towards another style of painting or subject.

    Empathy

    Empathy is the understanding of the problems and realities of the people and then designing the best product based on that understanding. AI can collect and collate data, but can never show the true nature of what drives human beings.  Data can show an individual’s activity spanning days or months, but cannot answer the ‘why’ of those activities.  

    It is this particular human quality that separates us from AI. It is this quality that allows humans to design and create products with a deeper informed decision.

    Mind Theory

    Human psychology is a web of emotions that affect thought and behaviour. For AI to replace creativity, it would need the capability to comprehend human complexities and make decisions based on self-reflection. Currently, this is beyond the AI technological brilliance.

    Conclusion

    The superior intellect of human beings has led to the invention of Artificial Intelligence. Yet, it is a system that is based on rules and algorithms and built-in data. It is a system that relies on those very rules and algorithms to process the data that has been fed to it. Can it collate, relate and process data faster than human beings? Without a doubt. Can it scale imaginative heights and then further push its limits? No.

    Human beings are not only gifted with intelligence but a natural curiosity to expand and grow. Continually push limits. Consistently evolve. AI is a tool that has been created to assist in our journey towards that excellence. Nothing more, nothing less. AI is a convenience that we created so we may continue to excel at our own imaginative brilliance.

    FAQs

    What jobs will AI take over?

    Customer service executives, Bookkeeping and data entry, Proofreading, Manufacturing and pharmaceutical work, Retail Services, and Courier services.

    What jobs will AI not take over?

    Human resource managers, Writers, Lawyers, Psychiatrists, and Event planners are some of the jobs AI will not take over in of near future.

  • Why Artificial Intelligence May Need Regulation?

    The article is contributed by Biswajit Das, Founder – Brandintelle Services

    Businesses & governments cannot do without AI/ML. Yet if we take it too seriously we may be misled, sometimes with very serious effects. But the reality is that in future, both governments & corporations may have to appoint AI/ML ombudsmen to check & control AI/ML algorithms.

    We have all faced occasional inquiries from our respective Direct & Indirect Tax Departments pertaining to a past period – which suggest that we have evaded taxes. The notice further asks us to prove that we are not evaders by furnishing documents that we had already furnished years ago. These are the results of AI/ML algorithms which are run by Tax Departments on the vast amounts of data that they have aggregated. In most cases, they serve as irritants, forcing citizens to submit the same documents multiple times at their own time & cost.

    Apart from the stress that this generates on semi-literate or otherwise challenged taxpayers, there is the odd case where the allegation by the algorithm can be of a more serious nature – without any justification. Repercussions of such AI/ML “activism” can be far more serious in-patients medical records as the following case shows.

    In 2021, Wired magazine reported a case of a patient who was suffering from a chronic condition which caused her great pain. Although the situation was not critical, the medicines were clearly not working. And surgery was very risky. To alleviate her pain, her physician naturally regularly prescribed opiates as painkillers. for multiple years.

    After many years, her physician recommended a hospital visit – for a second opinion as well as a possible alternate treatment. The patient visited & was asked to register as an in-patient for some examinations. She was accommodated & tests were conducted. Meanwhile, she ran out of her opiate painkillers & asked for a fresh prescription. This was a normal request as far as the patient was concerned – but it resulted in a deadlock situation. The hospital did not prescribe the medicine & nor did it give any reason. As soon as the tests were completed, they requested her to leave the hospital as they could not treat her any longer. Upset & perplexed, the patient went home & asked for an appointment with her regular physician. But she was in for a rude shock! Her physician refused to treat her. After much pleading, she was able to extract the reason – her identity was “blacklisted” as a substance abuser and on the basis of this, the medical profession was practically asked to boycott her. It took her many months to reverse the situation.

    What had happened behind the scenes just before this period is interesting. The hospital had signed up to outsource its Hospital Management System along with Electronic Medical Records to a third party along with a group of regional hospitals & regional physicians. The third party managed to aggregate patient medical records from all the hospitals, & physicians into a data lake. And as is the custom today, built some “intelligence” into its Hospital Management System with AI/ML. The algorithm that was published had an inbuilt logic that apparently categorised all prescription opiate users as “substance abusers” if they used opiates for more than a certain (undisclosed) period! The Hospital Management software automatically “blacklisted” such patients & barred them from any medical treatment!

    Current & future generations may rely on AI/ML as the ultimate decision-making tool. But in reality, AI/ML simply points to signs, trends & predictions all based on applied statistics (from the eighties & earlier!) which are applied to available historical data. This was not possible till the price-availability of computing & storage power crossed a threshold level – which happened in the last 5 years.


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    But here’s the thing: both data & algorithms are prepared by human beings. Therefore both are imperfect. And to make it worse, both data & algorithms are ‘opaque’ to end-users, making some victims & others perpetrators!

    Yet we tend to treat the predictions & pointers as though they were the Gospel truth!

    While these nudges & prediction techniques work in general, it can be fatally wrong at times. As the adoption of AI/ML proliferates, there will be a need to appoint regulators & ombudsmen who will have the right to examine & override decisions taken based on AI/ML algorithms.

  • 7 Great Industries in The United States To Get a Job

    If you are still looking for a job, here’s some good news for you! The United States is home to over a million different companies – and while many of them are small startups, others are well-known brands – Amazon, Apple, Disney, and Starbucks, for example. Many of these businesses have been around for a long time, some for more than a century. If you’re looking for a job and would like to work in a certain field ranging from tech to healthcare to hospitality and so on, there are many industries you can choose from. Here’s a look at some sectors with the greatest potential for growth through 2022.

    Top Industries to Get Job in The United States

    1. Healthcare
    2. E-commerce
    3. Renewable Energy
    4. Computer Systems Design and Related Services
    5. Education
    6. Tourism
    7. Artificial Intelligence

    Top Industries in the United States

    Healthcare

    Healthcare Industry Expenditure in The US
    Healthcare Industry Expenditure in The US

    There are many reasons to consider a career in the healthcare industry, but chief among them is demand. According to the Bureau of Labor Statistics, approximately 18 million new jobs will be created between now and 2022. Some of these positions will require formal education, such as registered nurses and physicians, but others do not. In addition, Healthcare support occupations — including home health aides — are expected to grow by 28% during this period.

    Many people think of doctors and nurses as the main providers of health care. Still, many other types of professionals can enjoy good salaries and job security. Those interested in medicine but don’t want to spend years in medical school consider becoming a physician’s assistant or nurse practitioner. Also, think about becoming a pediatric nurse practitioner or a pediatrician’s assistant if you like working with kids.

    If you don’t want to practice medicine, consider teaching. There is a growing demand for assistant teachers who help to train nursing students.

    E-commerce

    e-commerce Estimated Revenue In The United States
    e-commerce Estimated Revenue In The United States

    The consumerization of technology, new online payment methods, and the proliferation of mobile devices has accelerated the pace of e-commerce. The trend is clear — more and more people are shopping online every year.

    E-commerce is in the midst of a major transition. Just a few years ago, most e-commerce was conducted through desktop browsers. In 2022, according to Forrester Research, e-commerce will account for 11% of all retail sales, and 80% of that will be conducted via mobile devices.

    This means that brick-and-mortar stores will have to adapt to an increasingly mobile world, and that means investing in mobile apps and other technologies designed to support commerce on the go.

    eMarketer forecasts that U.S. e-commerce sales will surpass $600 billion by the end of 2022 — a 20% increase from the 2018 year — and will account for more than 18% of all retail sales in the country.


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    Renewable Energy

    Renewable energy Production Consumption in The United States
    Renewable energy Production Consumption in The United States

    Among the fastest-growing sectors in the world – renewable energy is an industry like any other. It can make or break a country’s economy.

    Renewable energy sources include solar, wind, hydroelectricity, biomass, and geothermal. These industries have been growing greatly over the past decade and will continue to grow in the coming years.

    The industry is booming, which means that the best people are already working there. However, those who want to make a difference will find it highly rewarding.

    The renewable energy industry is expected to grow at an annual rate of 22% in 2022. That includes solar power, wind power, biofuels, and other sources of green energy. So, even if you’re just starting, you can get into the renewable energy industry.

    Revenue of computer systems related services NewYork
    Revenue of computer systems related services NewYork

    Computer systems design and related services companies help other businesses with computer networking, maintenance, programming, and other associated services. The computer industry has already seen substantial growth in recent years. Still, the future looks even brighter as more businesses rely on computers for their daily work.

    Employment opportunities in this field are expected to be particularly strong for those with a bachelor’s degree or higher because many companies prefer to hire individuals who have completed an accredited program. The industry has grown speedily in the last few years at an impressive rate of 5.3%. This rate is expected to grow even faster in 2022 and beyond.

    According to the BLS, computer systems design is one of the fastest-growing jobs in America. The growth will be driven by businesses that want to make their operations more efficient and lower costs by outsourcing computer-related services.

    Employment in this industry has grown an average of 6.4% annually since 2010. Its projected growth rate for 2022 is more than four times that. The Bureau of Labor Statistics report says the computer systems design industry is set to grow by 22% in 2022, increasing the number of jobs to 1.2 million. In addition, the industry pays an average salary of $95,270.

    Education

    Educational Support Industry in The United States
    Educational Support Industry in The United States

    The education industry is a great industry due to its stability and room for growth. Many jobs in the education industry are necessary and cannot be outsourced, which means that plenty of opportunities exists in this field. Consider taking a course or degree related to teaching, human resources, or school administration to get into this industry.

    Experts predict that education will stay hot next year thanks to shifting demographics and technology.

    With baby boomers retiring and the economy improving, an estimated 3.2 million jobs will be added to the American workforce by 2022. That’s a lot of new workers, but it’s not all good news: According to a report from Georgetown University, 65% of jobs will require post-secondary education.

    According to BLS projections, education services will also grow substantially over the next 10 years. Thus, if you have an idea for a teaching tool, or other education-related product or service, now may be your chance to pursue it.


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    Tourism

    Tourism market in The United States
    Tourism market in The United States

    The tourism industry is one of the most exciting industries that one to get into. As people become more wealthy, they become more willing to spend money on leisure activities and experiences rather than products. People tend to spend money on experiences rather than products.

    To provide these experiences, the tourism industry needs a lot of employees. For example, it needs tour guides and other staff members to run its tours. It also needs marketers, logistics staff, and customer support personnel to ensure that its customers have a good time.

    Tourism and leisure are expected to experience the most growth of any industry in the U.S. over the next decade. Analysts expect it to add more than 1.2 million jobs between 2016 and 2026, with an average annual increase of 2%. It’s already one of the nation’s largest industries, employing roughly 11 million people in 2017, according to the Bureau of Labor Statistics (BLS).

    In addition, as the importance placed on experiences continues to grow, opportunities within the tourism industry are likely to increase as well. This means that you are likely to have good job security in this industry.

    Artificial Intelligence

    The future is here. If you want to be part of the next generation of tech, AI is the industry that is shaping the near future.

    If you’ve ever asked Siri or Alexa a question, used Google Maps to get somewhere, or bought something online based on a product recommendation, you’ve tapped into the power of artificial intelligence. This technology uses software and algorithms to solve problems that once required human intelligence. And it’s only going to get more sophisticated in the future. By the end of 2022, AI will help companies increase their productivity by 40%.

    A few big players lead the way for AI – IBM and Microsoft have large investments in AI research and development. But smaller companies are also making waves in this field: In 2017, Apple became one of the first tech giants to focus on ethics in AI Companies like Facebook are developing their own AI programs for chatbots and product recommendations, while DeepMind is researching how AI can predict diseases before they start.

    Artificial intelligence (AI) is a broad research field applied to many industries. AI is often defined as machine intelligence that mimics human thinking and decision-making to solve complex problems. According to an April 2017 report from McKinsey Global Institute, artificial intelligence could contribute $13 trillion to the global economy by 2030.

    Conclusion

    These are the best industries to get into. Your future career is waiting for you. These were some of the few great industries that will continue to grow strong in the years to come. Are you still on the fence? Consider each of these fields further and reach a decision that best fits your career aspirations. Good luck!

    FAQs

    What are the top industries for employment opportunities in the US?

    Top industries that have huge job opportunities in The United States are:

    • Healthcare
    • E-commerce
    • Renewable Energy
    • Computer Systems Design and Related Services
    • Education
    • Education
    • Tourism
    • Artificial Intelligence

    What jobs are most in-demand in the US?

    The most demanding jobs in the US are:

    • Registered Nurse
    • Software Engineer
    • Information Security Analyst
    • Occupational Therapist
    • Web Developer
    • Data Scientist
    • Solar PV installers
    • Wind Turbine Service Technician

    What is the biggest industry in the US?

    The top three major industries in The United States are:

    • Service Industry
    • Manufacturing Industry
    • Agriculture
  • List of US Agritech Startups Transforming Farming

    Farm Bot made a splash in the news, but it’s far from the only farming startup working directly with farmers to improve farming practices. Robots are taking over farms – US tech startups want to bring automation to farms. Robots are the latest farmhands in a resurgence of interest and investment in agricultural tech. Farms are getting into computers and IT once again, with innovations made possible by improvements in sensors and semiconductor technology. Recently, a new wave of tech startups is working hard to automate agriculture with robots and AI. For example, a technology that hoes fields using computer vision autonomously identifies weeds and destroys them with targeted amounts of herbicides or pesticides. It can do this much more cost-effectively than humans can.

    How are robots transforming work on farms?
    What are the advantages of robots on farms?
    Top Technologies Ruling Agriculture

    1. FarmBot – The First Open-source CNC Farming Machine
    2. Abundant Robotics – Apple Harvesting Robot
    3. Augean Robotics – Earth-friendly Weed-killing Robots
    4. Boston Dynamics – Atlas Robot
    5. Iron Ox – Autonomous Growing Facility
    6. Blue River Technology – A Technology That Hoes Fields Using Computer Vision

    Future of Robots on Farms

    Top Agritech Startups 2022

    How are robots transforming work on farms?

    Farming is a highly competitive industry. Farmers are under constant pressure to grow more crops and livestock while keeping production costs low. As the world’s population increases, farms will need new ways to boost productivity and efficiency. This may include adopting technologies once thought of as science fiction, such as self-driving tractors and robotic milking machines.

    The machinery and technology that farmers use are constantly evolving to make them more efficient. This can positively impact the environment, but it’s also led to some negative consequences, such as the loss of many jobs in farming.

    Farmers have invested in drones for aerial imaging, GPS-guided tractors, and other technologies to boost efficiency and reduce labour costs in recent years. In the next decade, robots may be able to help with more complex tasks such as weeding, harvesting and pruning.

    The seed-planting machines can operate at night and in the rain, so they don’t have to wait for ideal weather conditions. It’s all part of the farm’s efforts to remove humans from the equation and use technology to boost productivity.

    The advances in agriculture have been nothing short of spectacular. Farm equipment gets more powerful, precise and efficient every year. Farms are becoming more automated in almost every way imaginable. Barns have become more comfortable and efficient for animals. Crops are being grown in vertical greenhouses and hydroponically — without soil. There are even robots that milk cows now.

    What are the advantages of robots on farms?

    Robots can do the farm work without getting tired. Even if they get damaged, you can easily repair them. Robots are more accurate than humans, and they can do a lot of work in a short period. Unlike humans, robots don’t need water or food to survive. Machines don’t have to rest day or night. They can work 24/7. Here are a few of the top advantages of having robots on the farm.

    More efficient work

    Robots can be programmed to pick the fruits and vegetables in a certain way so that only the best produce is selected and sent to market. This means that farms will waste less food. After all, it will no longer need to be picked by hand, which requires more employees and results in wasted produce because it was picked incorrectly or bruised during transport.

    Reduced labor costs

    Robots are becoming more common in factories because they can perform more efficiently than human workers. The same is true on farms. Robotic equipment can be programmed to handle tasks requiring precision and speed while also performing repetitive tasks without getting tired or injured. This reduces labour costs for farmers with robotic equipment deployed on their farms.

    Reduced risk of injury

    Farms pose many potential hazards for humans – from sharp machinery and heavy equipment to dangerous chemicals and inclement weather conditions. By automating certain tasks that require human interaction with these dangers, you can reduce the risk posed to your employees – keeping them safe from harm.

    Increased productivity

    As well as working longer hours than humans for minimal cost, robots can also increase productivity levels by performing tasks faster and more accurately than their human counterparts.

    They’re cheap

    Robots can be programmed to do a certain job, and once they’ve been programmed, they won’t need any more training; they’ll just do the job repeatedly without getting tired or bored.

    They’re fast

    Robots can work 24 hours a day, seven days a week, without any breaks. This means that a farmer can get more work done in less time. In addition, the faster you complete your work, the less money it will cost you in labour costs and equipment wear and tear.


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    Top Technologies Ruling Agriculture

    Big data and machine learning algorithms can help farmers increase harvests while reducing their environmental footprint. The conventional farming techniques and methods that we’ve used for decades are becoming obsolete — machines and computers are taking over farms. So what is happening with farm bots? Let’s look at these companies and their technologies.

    FarmBot – The First Open-source CNC Farming Machine

    FarmBot - Agritech Startups in the US
    FarmBot – Agritech Startups in the US

    FarmBot is an open-source CNC farming machine and software package designed for small-scale personal farming. It uses a web application and Arduino-powered firmware to control a set of stepper motors that move a tool head around a patch of soil, performing the various tasks required for farming. The goal is to empower people to grow food with confidence in their backyard or community garden by offering you an easily deployable, scalable, and customizable robotic gardening system.

    The Farmbot team’s vision is that one day farmers and every person will have access to healthy food grown with love at home, in their community gardens, and on local farms — regardless of their background or income.

    Abundant Robotics – Apple Harvesting Robot

    Abundant Robotics - Agritech Startups in The US
    Abundant Robotics – Agritech Startups in The US

    Abundant Robotics is working on a harvesting robot for apples. The company’s prototype can identify and pick apples with more precision than a human.

    The robot uses a vacuum system to pick the fruit from the tree. Technology does not appear to damage the apple or the tree. However, the company says that it needs further testing before making this technology commercially available.

    The robot uses a combination of cameras and computer vision software to find good apples on trees and suction cups to grab them without damaging them gently. It can pick an apple every 12 seconds and works day and night.

    The technology is limited to apple growers in Washington state but hopes to develop robots that can harvest various soft fruits and vegetables.

    Augean Robotics – Earth-friendly Weed-killing Robots

    Burro formerly (Augean Robotics) - Agritech Startups in The US
    Burro formerly (Augean Robotics) – Agritech Startups in The US

    Burro, formerly known as Augean Robotics wants to replace herbicides and manual labour with fleets of robots that patrol vineyards, orchards, and farms.

    The Augean robot looks like a mini tank on treads. It has two wheels, each with vertical blades that cut down weeds as it moves along the rows. It also sprays vinegar to keep weeds from growing back.

    The idea is that farmers would use a fleet of wheeled drones that would be able to successfully detect weeds and kill them, allowing farmers to increase their crop yields and earn big.

    Boston Dynamics – Atlas Robot

    Boston Dynamics - Agritech Startups in The US
    Boston Dynamics – Agritech Startups in The US

    Boston Dynamics’ Atlas robot can do an impressive range of activities, from tai chi to parkour. And now, it can help out around the farm.

    Boston Dynamics has released a video showing Atlas carrying a crate of lettuce heads across an obstacle course and then placing them in a box.

    Atlas is a bipedal robot that stands 5-foot-9 and weighs 180 pounds. It’s designed to tackle human-like tasks, including lifting heavy objects, opening doors, and walking in rough terrain.

    In the latest video, Atlas steps over hurdles positioned in its path. They then balanced on one foot while picking up the crate using the other foot. It then bends over to place the container into a box.

    Iron Ox – Autonomous Growing Facility

    Boston Dynamics - Agritech Startups in The US
    Boston Dynamics – Agritech Startups in The US

    Iron Ox, a California startup, deploys autonomous growing, harvesting, and delivery for local farms.

    The Iron Ox approach has some similarities to the indoor farms you’ve probably heard about: The produce is grown in a warehouse-like building that allows for year-round cultivation.

    But there are several significant differences. First of all, Iron Ox’s facility isn’t stacked with trays of plants under grow lights. Instead, it uses hydroponics, which involves directly exposing the plants’ roots to nutrient-rich water rather than soil. The company says this approach allows its system to cultivate plants with the same taste and nutritional qualities as those grown in open fields or greenhouses but use 90% less water and 99% less land.

    The company grows greens in climate-controlled shipping containers (they are, after all, based in Silicon Valley) using an AI system called Angus. Then, according to each plant’s specific requirements, Angus monitors the plants’ needs and sends them what they need — water and nutrients.

    Blue River Technology – A Technology That Hoes Fields Using Computer Vision

    Blue River Technology - Agritech Startups in The US
    Blue River Technology – Agritech Startups in The US

    In the 1950s, when a man named John Deere invented the first tractor, he probably did not think that a self-driving tractor would be hoeing fields one day.

    Blue River Technology is a tech company that uses computer vision to help farmers make faster and better decisions. As a result, farm management should be more economical and less environmentally harmful. Still, many require regular manual inspection of crops—a time-intensive process with a high margin of error. Blue River Technology has created see-and-spray technology that allows its machines to distinguish between crops and weeds. Once they know what’s what, they can spray herbicide at just the right moment through real-time analytics software.

    The idea is cashier-less stores by Amazon. The company has created see-and-spray technology that allows its machines to distinguish between crops and weeds. Once they know what’s what, they can spray herbicide at just the right moment. This will enable farmers to save money by only spraying the plants that need it.

    The promise of Blue River’s tech is huge: less waste, more productivity, and lower costs for farmers.


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    Future of Robots on Farms

    The future of farming looks like a science fiction movie, with robots planting crops, drones monitoring fields and satellites providing information from space. But are robots taking over farms?

    Not quite yet. Despite the many advancements in technology, there is still a significant need for people on farms. Many tasks still require a human touch, like planting delicate crops and harvesting them.

    The world of farming is changing. Advances in technology, including robots that can be programmed to work together, have allowed those working in the fields to get more done with less labour. These innovations are making farming more efficient and, at the same time, cheaper for farmers.

    Farm automation is already revolutionizing the way farming is done. For example, robots are now being used to help farmers plant and harvest crops more efficiently. The future of agriculture is even more exciting, as modern technology will soon allow farmers to do things they couldn’t even dream possible with no human intervention at all.

    Conclusion

    US Tech Startups making Farming Robots will change the world with technologies of the future.

    Innovation can make businesses more efficient, with substantial cost savings. Farms could benefit immensely from automation. Their use has already helped farmers, and their numbers are snowballing. Automating farming will lead to immense cost savings, which will allow businesses to focus more resources on the more pressing issues they face. Agricultural robots are already here, and there’s no sign that they’ll stop making life farmer’s life easier any time soon. We should pay attention now because agricultural automation is on the horizon. Robots will revolutionize farming, and they will do it faster than you’d think. Fields that formerly needed thousands of workers to plough will soon be mechanized. Instead of being job killers, AI farms could provide work for thousands of people in the future, managing the robots and maintaining them, among other things. Automating farming will lead to immense cost savings, which will allow businesses to focus more resources on the more pressing issues they face. Humanity will be better off with robotics in the future, and the world is excited to witness this.

    FAQs

    Are robots used for agriculture?

    Robots are used for many purposes in agriculture. Some examples are:

    • Harvest Automation
    • Autonomous Growing
    • Orange Harvester
    • Apple Harvester
    • Autonomous mowing
    • Lettuce bot
    • Weed-killing

    Which are the companies working for robotics farming?

    Some of the best Robotics Companies working for robotics farming are:

    • Blue River Technology
    • Harvest CROO Robotics
    • Iron Ox
    • Boston Dynamics
    • Trace Genomics
    • Burro Robotics
    • FarmShots
    • Abundant Robotics

    What are the top technologies ruling Agriculture?

    Top Technologies ruling agriculture are:

    • FarmBot – The First Open-source CNC Farming Machine
    • Abundant Robotics – Apple Harvesting Robot
    • Augean Robotics – Earth-friendly Weed-killing Robots
    • Boston Dynamics – Atlas Robot
    • Iron Ox – Autonomous Growing Facility
    • Blue River Technology – A Technology That Hoes Fields Using Computer Vision
  • Upskilling for Women in the Technology Sector in an Era of AI

    The article is contributed by Minal Sonawane – Software Test Solution Architect, AFour Technologies.

    As businesses build back after the disruptions of the pandemic, there is considerable interest in transforming work structures to be more robust and more dynamic than they were before. Precisely, businesses are endeavoring to build more equitable workplaces for women, who have historically been excluded from advancing as much as their male peers. As AI enters and alters business processes in myriad ways, upskilling will emerge as a crucial tool in addressing gender inequality in the tech space. Here, we briefly examine how this can come about.

    Gender Disparity in Tech

    Research consistently shows that diverse teams perform better, have higher satisfaction rates, and stay on longer. And yet, industries like manufacturing or IT remain heavily male-dominated. According to a joint study by LinkedIn and the World Economic Forum, women make up only 25% of the STEM (Science, Technology, Engineering, and Math) workforce. Moreover, only 22% of artificial intelligence (AI) professionals and 12% of machine-learning (ML) experts are women. Even if they have the same qualifications, men frequently reach executive positions faster than women in the workplace. Many companies also hesitate to help women earn senior tech positions because of preconceived notions about their skills or assumptions about marriage and family coming first for women.

    These issues were exacerbated when Covid-19 struck, and everyone was forced to stay at home. As primary caregivers, the duty of looking after children during the lockdown fell mainly on women, many of whom had to deal with burnout owing to the difficulty of balancing work commitments with family obligations. In particular, a 2021 Women@Work study by Deloitte revealed that 83% of women in tech had an increase in workload along with household duties, while only 38% felt that their organization had given them adequate support. Overall, a recent Citigroup study concluded that about 44 million people would lose their jobs due to the pandemic, of which 31 million would be women – a highly concerning disparity.

    With the advent of AI into everyday business tasks, the respective roles of humans and machines are undergoing significant shifts. Routine tasks are being delegated to software, while advanced skills like machine learning and deep learning are highly demanded. Partly because of the educational gaps between the genders (traditionally, boys are encouraged to take up science while girls are pushed towards the arts and domestic studies) and partly because of male-centric preferences at work, it is women who mostly hold the administrative, clerical and routine job positions that are now being routed to AI. Moreover, there are no clear pathways to help women transition from these routine jobs and towards more complex and lucrative ones related to tech and its applications. As a result, they either end up quitting the workforce or staying on in low-paying jobs that do not let them reach their potential.

    Upskilling as an Equalizer

    Online learning has expanded considerably since the pandemic, which means that accessing high-quality educational content and insight from experts is easier than ever. Upskilling through online courses allows employees to stay up-to-date on rapidly evolving tech trends and pick up valuable new skills from scratch. For women employees, upskilling safeguards them against redundancy and helps them become more valuable assets in terms of the ideas and creative approaches they can bring to the table. In particular, online learning allows them to pick up skills at their own pace and at affordable rates, which is a boon for women juggling household duties and/or those in less lucrative jobs. This way, they can aim for positions that men have traditionally occupied and come into their own as creative contributors.

    Upskilling, indeed, makes employees of all genders more effective and for an emerging and nuanced field like AI, one needs as many talented team members as possible. It is thus in the company’s interest to offer AI-related upskilling opportunities, from online learning pathways to live projects to shadowing opportunities with senior experts. In particular, leaders should invest in training programmes for women in tech with special technical courses and mentorship from senior women leaders. There should also be exceptional support for women compelled to take time off during the pandemic so that dedicated workers can feel like they are valued regardless of their setbacks.


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    The Way Forward

    It is still early days in the “AI-fication” of industries, and effective intervention on a company’s part can go a long way toward reversing gender disparity trends. Comprehensive upskilling opportunities and career transition pathways can help women pick up the skills they may have been traditionally denied and contribute side-by-side with male peers. Companies have already seen the efficacy of flexible work models and should invest in similarly inflexible growth models that help employees – especially women – move upwards into tech roles where talent and interest count for more than background or work history. Thoughtful efforts in this regard will help redress gender disparity and exclusion at work, not just post-pandemic but for all time.

  • How AI is Transforming Investment Decision Making? | AI Use Cases

    The article is contributed by Andesh Bhatti –  Angel Investor & Founder of Collectcent.

    The investment management sector is witnessing what is perhaps its most volatile moment in history. The investment landscape has changed and changed for good at that.

    Investment is no longer an exclusive habit of the rich and powerful, but rather one that’s becoming more widely available as new disruptive technologies make it more and more accessible to the general public. In fact, investment opportunities can now be taken advantage of with the tap of a smartphone because of the rise in demand for digitally facilitated, easy-to-understand financial services.

    Although all these new technologies have the potential to revolutionise and improve the investment process, artificial intelligence (AI) is the one that offers the most potential. The technology encompasses a wide range of techniques for simulating human-like intelligence on a machine. For investors who have until now ventured on the precarious investment terrain relying primarily on their gut instincts and personal assessments, artificial intelligence offers a whole slew of opportunities.

    Gartner predicts that by 2025, artificial intelligence (AI) and data analytics will be used to inform more than 75% of venture capital (VC) and early-stage investor assessments.

    The Inner Voice Conundrum and Its AI Resolution

    Investors who succeed in their ventures are often believed to have a sharp intuition. That’s because their capacity to make financial decisions is based on largely qualitative data like management expertise, industry cycles, strength of research and development, and labor relations; only after that is it abetted by the quantitative data provided by the financial specifics of any business. However, it’s difficult to measure an inner voice, especially when that voice is developed largely through personal experience. And, of course, it also does not give a guarantee of success. Consequently, the role it plays in investors taking financial decisions is decreasing.

    The AI Answer

    Rising data analysis capabilities are fast directing early-stage investing strategies away from personal judgment and qualitative decision making and toward a more sophisticated quantitative process. Data from websites like LinkedIn, Crunchbase, and Glassdoor, as well as third-party data marketplaces, will be a big part of this process. They are already giving rise to sophisticated models that can better identify the feasibility, proposal, and prospective outcome of an investment. The result being that questions like when to invest, where to invest, and how much to invest are on the verge of becoming practically automatic.

    But that’s on optimizing the quantitative process alone. AI is also enabling the metrics for measuring success based on qualitative factors.

    AI technology is renowned for its capabilities of predicting future behaviour and delivering insights into client preferences. Natural language processing AI that can discern features about an individual from real-time or audio recordings can further be used to generate unique profiles, now with barely any human assistance. Based on job history, field experience, and previous business performance, AI algorithms can soon be utilised to estimate the likelihood of investment success reliant on individuals.


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    The Use Cases for AI in Investment Management

    AI can be used in three stages of the investment decision making:

    Pre-trade

    To find and analyse investment opportunities, analysts devote a large amount of time to gathering, sorting, and organising relevant data. Consequently, a substantial part of their efforts is spent on data that is later found to be of little value.

    Natural language processing (NLP) AI can handle a big part of this job, as it can take in large amounts of data from multiple sources, scan for trends and patterns, and then assign a score to each relationship it uncovers. Using these tools can significantly minimise the amount of time analysts spend in this phase, allowing them to focus on data that has the greatest potential for better discoveries.

    At the moment of truth

    Although it is up to the investor to make buying, selling, or holding choices, NLP AIs can assist in this. Relying on AI results blind sightedly is not what most investors are going to buy into. NLP can help explain the drivers of an AI decision engine and give an unbiased report that explains the decision in detail, including all the countervailing elements. This can further enable managers to deep analyse a trade and approve or reject it.

    Post-investment

    NLP engines can leverage structured data inputs to create performance attribution reports and periodic investor reviews. The technology has the potential to increase the speed, precision, and cost of creating reports based on the performance and strategy of the investments made.

    Conclusion

    The use of AI by investment managers is quick reaching a point where it could provide a competitive edge for a long time to come, by enabling better investment possibilities as well as increased operational efficiency. Needless to say, it has the potential to revolutionise the investment decision process, and by relation, the world of growth and innovation.