Tag: DeepMind

  • Pushmeet Kohli: The Mind Behind DeepMind’s Most Ambitious AI Projects

    When people talk about super-smart AI that can match or even surpass human experts, Pushmeet Kohli is often the quiet genius behind those advancements.

    As the head of research at Google DeepMind, he leads groundbreaking projects like AlphaFold (which solved the mystery of protein folding), Gemini (DeepMind’s version of ChatGPT), and important AI safety measures to keep AI under control. His work isn’t just technical; it’s about shaping the future of AI with science, ethics, and real-world benefits.

    Pushmeet combines brilliance with humility from his early days at Microsoft to helping set global AI policies. While AI moves fast, he stays focused on one goal: creating AI that helps everyone. Let’s explore the story of the mind powering some of DeepMind’s most ambitious AI missions.

    Pushmeet Kohli – Biography

    Name Pushmeet Kohli
    Nationality Indian
    Profession VP Science and Strategy Initiatives at Google DeepMind
    Education Ph.D. in Computer Vision and AI, University of Oxford
    Notable Roles Former Director of Research at Microsoft Research Cambridge

    Pushmeet Kohli – Early Life and Academic Brilliance
    Pushmeet Kohli – Career Beginnings
    Pushmeet Kohli – Pioneering AI Research at DeepMind
    Pushmeet Kohli – Pioneering AI Research at DeepMind
    Pushmeet Kohli – Key Contributions
    Pushmeet Kohli – DeepMind Research Philosophy
    Pushmeet Kohli – Awards & Recognitions

    Pushmeet Kohli – Early Life and Academic Brilliance

    Growing up in the serene hill town of Dehradun, Pushmeet Kohli once dreamed of becoming a teacher. Reflecting on his journey, he shares, “I find the role of teachers in society a very important one. The impact they have on shaping and influencing people cannot be overstated. Currently, I am teaching machines. Maybe at some point, I would like to become a teacher in a school or university.”

    He completed his undergraduate studies in computer science before earning a fully funded scholarship to pursue his doctorate at the prestigious University of Oxford. There, his research focused on probabilistic models for computer vision, an area that would later become central to the rise of intelligent machines.

    His early work on Conditional Random Fields (CRFs), Markov Random Fields (MRFs), and energy minimization techniques not only earned citations across top-tier AI conferences but also paved the way for practical applications in image segmentation, object recognition, scene understanding, and robotic vision.

    Pushmeet Kohli – Career Beginnings

    Pushmeet Kohli spent a decade at Microsoft, where he led the Cognition research group and contributed across its global labs in Seattle, Cambridge, and Bangalore. He also served as a trusted technical advisor to Rick Rashid, the then Chief Research Officer of Microsoft. 

    His research during this time focused on advancing Intelligent Systems and Computational Sciences, with key contributions in Machine Learning, Computer Vision, Game Theory, and Information Retrieval.

    At Microsoft, Pushmeet played a pivotal role in bridging foundational AI research with real-world applications, helping shape projects that combined deep theoretical work with practical innovation. His interdisciplinary approach and ability to translate complex algorithms into scalable solutions earned him wide recognition within the AI research community.

    In addition to machine learning information retrieval models. He has published papers in conferences on computer vision, machine learning, robotics, and artificial intelligence. The areas of intelligence systems and computational sciences are among his research interests.

    Pushmeet Kohli – Pioneering AI Research at DeepMind

    Pushmeet Kohli heads the AI for Science initiative at DeepMind, where he leads groundbreaking work on systems like AlphaEvolve, an AI that can discover novel algorithms and even prove mathematical theorems that have stumped experts for decades. 

    From improving matrix multiplication techniques developed over 50 years ago to generating interpretable code for complex tasks like data center scheduling, AlphaEvolve showcases a powerful fusion of large language models and evolutionary search. 

    He often breaks down the technical foundations of these breakthroughs and shares insights from collaborations with world-renowned mathematicians like Terence Tao. His work exemplifies how AI is now accelerating scientific progress in fields ranging from chip design to advanced materials science.

    Pushmeet Kohli played a key role in the development of AlphaFold, DeepMind’s groundbreaking AI system for predicting the 3D structure of proteins. The system’s impact was profound; its research paper became the most cited publication of 2021.

    Since its release, over 1.7 million researchers across 190 countries have used AlphaFold to advance scientific discovery, from engineering plastic-eating enzymes to accelerating the development of next-gen malaria vaccines.

    “This is just the beginning,” says Kohli, who believes AI will eventually pave the way toward building a virtual cell, a digital replica of life that could transform biomedical research by enabling biology to be studied entirely in silico, without relying solely on physical labs.

    Pushmeet’s current research spans a wide spectrum of cutting-edge AI domains. He is actively exploring 3D reconstruction and rendering, probabilistic programming, and building interpretable, verifiable knowledge representations from deep learning models. 

    His interests also extend to task-oriented conversational agents, machine learning systems for healthcare, and immersive 3D rendering and interaction technologies for augmented and virtual reality (AR/VR).

    Pushmeet Kohli – Key Contributions

    Pushmeet Kohli believes that AI has the potential to be one of humanity’s most powerful tools in understanding and shaping the natural world. One of Kohli’s major contributions is to AlphaFold, DeepMind’s breakthrough system that solved the long-standing problem of predicting 3D protein structures, transforming fields like drug discovery and molecular biology.

    In 2022, his team tackled another complex challenge: matrix multiplication. By gamifying the problem into a 3D board game called TensorGame, they discovered faster algorithms and addressed a 50-year-old open question in mathematics: how to multiply matrices in the most efficient way.

    Kohli is also fascinated by AI’s role in controlling fusion reactors. He calls DeepMind’s success in using AI to stabilize plasma in a reactor “surprising and powerful,” highlighting how far machine learning has come in real-world applications. Kohli remains deeply interested in the future of generative AI, viewing it as the next frontier in creativity, science, and intelligent systems.


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    Pushmeet Kohli – DeepMind Research Philosophy

    For Pushmeet Kohli, two things make DeepMind truly special. First, it’s the shared commitment to a bold mission, not just to solve intelligence, but to use it for the betterment of science and humanity. 

    Second, it’s the collaborative culture. Tackling complex, long-term scientific problems can often feel isolating, especially when few people truly understand the challenges they present. 

    But at DeepMind, that isolation fades. “You are surrounded by people who not only understand the problem but are equally passionate about solving it,” says Kohli. “It’s like working with a unified team that shares both the vision and the drive.”

    He sums it up with a powerful thought: “You are a product of your interactions.” And at DeepMind, those interactions are what fuel progress.

    Pushmeet Kohli – Awards & Recognitions

    1. Sullivan Doctoral Thesis Award: Pushmeet’s Ph.D. thesis, “Minimizing Dynamic and Higher Order Energy Functions using Graph Cuts”, won this prestigious award from the British Machine Vision Association.
    2. Runner-up, Distinguished Dissertation Award: His thesis was also recognized as a runner-up by the British Computer Society.
    3. Best Paper Awards: His research papers have received awards at several top-tier conferences:
    • ICVGIP 2006
    • ICVGIP 2010
    • ECCV 2010
    • ISMAR 2011
    • TVX 2014
    • CHI 2014WWW 2014
    • CVPR 2015
    1. Prolific Publications: Pushmeet has published widely across major AI and computing venues, including:
    • Computer Vision: ICCV, CVPR, ECCV, PAMI, IJCV, CVIU, BMVC, DAGM
    • Machine Learning & AI: NeurIPS, ICML, AISTATS, AAAI, AAMAS, UAI
    • Robotics & AR/VR: ISMAR
    • Computer Graphics: SIGGRAPH, Eurographics
    • Human-Computer Interaction: CHI, UIST
    • Media Recognition – His work has been featured in leading global media outlets such as:
    • Forbes
    • Wired
    • BBC
    • New Scientist
    • MIT Technology Review
    1. ACM Distinguished Speaker: Pushmeet is a recognized speaker in the Association for Computing Machinery’s (ACM) Distinguished Speaker Program, acknowledging his contributions to the global tech and research community.

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    FAQs

    Who is Pushmeet Kohli?

    Pushmeet Kohli is the Vice President of Science and Strategy Initiatives at Google DeepMind.

    What is Pushmeet Kohli’s educational background?

    Pushmeet Kohli holds a Ph.D. in Computer Vision and Artificial Intelligence from the University of Oxford, where he worked on probabilistic models like CRFs and MRFs that have since influenced modern AI research.

    What is AlphaFold, and how is Pushmeet Kohli connected to it?

    AlphaFold is an AI system developed by DeepMind that predicts 3D protein structures. Pushmeet played a crucial role in its development.

  • Top 10 Generative AI Companies in 2023

    With the launch of ChatGPT in November 2022, the focus on generative AI has increased. If there’s a talk about Generative AI around you, you might notice OpenAI or one of its products, say ChatGPT, being mentioned. Generative AI is a type of artificial intelligence that focuses on generating new data that is similar to existing data. This is typically done using deep learning algorithms such as generative adversarial networks (GANs) or variational autoencoders (VAEs).

    I’m quite impressed by what generative AI has achieved so far, especially in generating high-quality images, videos, audio clips, and natural language text.

    Multi-billion dollar business [processes] are being rewritten thanks to generative AI, says Shobhit Varshney, IBM Consulting.

    The ability of generative AI models to learn complex patterns and relationships between inputs and outputs makes it possible to produce diverse and highly accurate outputs that can be used in various fields including entertainment, education, advertising, marketing, finance, healthcare, and scientific research, to name a few.

    Generative AI models have achieved what was considered impossible five-six years ago. Creative labor which was once under the realm of humans, has been surpassed by machines. Machines can now create things entirely new – write code, poetry, and stories, design 3D products, and create images and videos with little to no human help. It is a rapidly evolving domain that has many potential applications and benefits for various industries and sectors. It is also a challenging and complex field that requires a lot of research and development.

    The impact of generative AI on our day-to-day life can be summed up by this response given by an employee at OpenAI answering the question “What would your life look like if we didn’t have OpenAI?”, ‘I wouldn’t know how to code’ (was the answer).

    This person might have studied computer science at school for instance but that’s not the point we are trying to make. Generative AI tools like ChatGPT can provide help with complex tasks at hand.

    However, there are concerns surrounding privacy, safety, fairness, bias, explainability, interpretability, accountability, and security when deploying generative AI systems.

    Generative AI has the potential to significantly transform our lives in numerous ways (good and bad). For example, generative AI algorithms can generate synthetic information from input data, creating realistic fake news reports, social media posts, deep fake videos, manufactured terrorist evidence, artificial radioactivity levels & nuclear reactor core temperature readouts influencing geopolitical decisions. By processing huge amounts of data, some call it “artificial general intelligence,” enabling them to handle problems as humans do.

    More worrisome is, “Hyperrealism in video manipulation” i.e., video manipulation with the use of technology to create videos that are so realistic that they are indistinguishable from real life. People should be worried.

    As deep fakes advance, people might eventually reach a point where they’re unable to discern whether certain types of information were generated by machines, resulting in misinformation spread more effectively, intensifying polarization trends previously magnified by filter bubbles’ reinforcement during post-truth era Facebook pivot to messaging monopoly (which is also a worrying trend). It is therefore essential to continue researching these issues to help balance the benefits of generative AI against potential risks and ensure their responsible use.

    Overall, generative AI shows great promise and holds significant potential, opening doors to new possibilities in many industries and disciplines.

    Let’s look at this list of the top 10 Generative AI companies dedicated to the research and development of Artificial Intelligence and Deep Learning:

    OpenAI
    DeepMind
    IBM Watson and Watsonx
    Alphabet (Google)
    Salesforce
    Microsoft
    Adobe
    Intel
    Writesonic
    NVIDIA

    OpenAI

    Company OpenAI
    Founders Elon Musk, Sam Altman, Ilya Sutskever, Greg Brockman, Wojciech Zaremba, and John Schulman
    Founded December 11, 2015
    Headquarters San Francisco, United States
    Top AI Generative Companies - OpenAI
    Top AI Generative Companies – OpenAI

    OpenAI is renowned for its work on generative language models and is quite popular with its overnight hit ChatGPT AI chatbot which amassed 1 million users within 5 days of its launch. Its GPT (Generative Pre-trained Transformer) series, including GPT-3 and GPT-4, has gained attention for its ability to generate human-like text and engage in natural language conversations. Before ChatGPT, OpenAI developed InstructGPT which became the basis of ChatGPT, a chatbot model, capable of taking user instructions that were absent in its GPT models.

    OpenAI’s models have been utilized for various applications, including content generation, language translation, chatbots, and its DALL-E project focuses on generating images from textual descriptions, allowing users to create unique and imaginative visual content which is also a great success.

    In 2023, OpenAI launched its latest product, the ChatGPT Plus, based on its GPT-4 LLM. However, it is not free for all users and you need to buy a $20/month subscription.

    DeepMind

    Company Google DeepMind
    Founders Demis Hassabis, Shane Legg, and Mustafa Suleyman
    Founded September 23, 2010
    Headquarters London, England
    Top AI Generative Companies - Google DeepMind
    Top AI Generative Companies – Google DeepMind

    DeepMind is a British artificial intelligence company that was acquired by Google in 2014 and its generative AI research spans various domains, including reinforcement learning, robotics, and healthcare. It has developed novel generative models and algorithms, such as the Deep Q-Network (DQN) for game playing and the Generative Query Network (GQN) for scene representation and generation. It aims to develop generative models capable of producing more complex and flexible outputs.

    IBM Watson and Watsonx

    Company IBM
    Founders Charles Ranlett Flint and Thomas Watson Sr
    Founded June 16, 1911
    Headquarters Armonk, New York, U.S.
    Top AI Generative Companies - IBM Watson and Watsonx
    Top AI Generative Companies – IBM Watson and Watsonx

    IBM has also been working on generative AI for many years, and they have made several significant achievements. Watsonx is their upcoming ‘enterprise-ready AI and data platform’ designed to multiply the impact of AI across your business. But IBM has been dedicated to AI and cloud computing for decades now.

    In 2014, IBM released Watson AI, a platform for building and deploying AI models. It combines generative AI techniques with natural language processing (NLP) and machine learning to provide advanced cognitive solutions for businesses across multiple industries and has been widely adopted across industries, including healthcare, finance, and customer service. Watson AI encompasses a suite of cognitive computing technologies and services that can derive insights from large amounts of structured and unstructured data.

    Later in 2017, IBM released Watson Assistant, a chatbot platform that can be used to create conversational AI experiences. WA is very popular and it is being used to provide customer service across the world. It was followed by the release of Watson Discovery in 2019, a platform for finding insights into data.

    Alphabet (Google)

    Company Alphabet
    Founders Larry Page and Sergey Brin
    Founded October 2, 2015
    Headquarters Googleplex, Mountain View, California, U.S.
    Top AI Generative Companies - Alphabet
    Top AI Generative Companies – Alphabet

    Alphabet has several generative AI technologies, including Google Brain and Google Translate. Google Brain is a research project that is focused on developing new AI technologies Translate can be used to translate text from one language to another. It uses a variety of AI technologies, including NMT, to provide accurate and reliable translations.

    Google Brain’s Generative Adversarial Networks (GANs) are a type of machine learning algorithm that can be used to generate realistic images, text, and other types of data. It also developed Transformers, a type of neural network that can be used for natural language processing tasks, such as machine translation and text summarization.

    Alphabet also developed NMT which uses neural networks to translate text from one language to another. Alphabet is best for scalability, and offers generative AI support in its cloud platform Vertex AI, as well as a generative AI app builder and generative AI features in its Workspace suite.

    In 2023, Google launched its generative AI chatbot Bard which it still calls an experiment. Bard AI can, like ChatGPT, can generate text, and creative content and provide information in a human-like text. You can access BardAI on its official website by login into your Google account.


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

    Company Salesforce
    Founders Marc Benioff, Parker Harris, Dave Moellenhoff, and Frank Dominguez
    Founded February 3, 1999
    Headquarters Salesforce Tower, San Francisco, California, U.S.
    Top AI Generative Companies - Salesforce
    Top AI Generative Companies – Salesforce

    Salesforce is a leading customer relationship management (CRM) platform that integrates generative AI algorithms into its CRM platform to enhance customer engagement and personalization. Through machine learning and natural language understanding, Salesforce’s generative capabilities enable features like automated email response generation, chatbot interactions, and predictive analytics to improve the overall customer experience.

    The integration of AI into Salesforce’s CRM platform provides customers with an enhanced level of service that would be impossible without this technology. Automated emails can respond quickly to inquiries while chatbots provide more personalized responses in real-time than could ever be achieved by manual processes alone. Predictive analytics allows for better segmentation of customers based on their needs or behaviors which leads to improved targeting strategies for marketing campaigns as well as other initiatives such as product recommendations or upsell opportunities tailored specifically for each user.

    Microsoft

    Company Microsoft
    Founders Bill Gates and Paul Allen
    Founded April 4, 1975
    Headquarters One Microsoft Way Redmond, Washington, U.S.
    Top AI Generative Companies - Microsoft
    Top AI Generative Companies – Microsoft

    Microsoft has been at the forefront of generative AI development for many years, and they have made several significant achievements. In 2017, Microsoft released Azure Machine Learning, a cloud-based platform that enables users to build and deploy their machine learning models. It is now one of the most popular platforms in the world and is used by many companies developing generative AI solutions. Additionally, Microsoft developed Power BI as an enterprise intelligence tool to help businesses analyze data more effectively and generate reports automatically.

    More recently in 2020, Microsoft partnered with OpenAI to release GPT-3 which has facilitated numerous applications such as chatbots or content generators for creative writing tools among others. This powerful language model can be trained on large datasets quickly so that it can produce better results than traditional methods like natural language processing (NLP). GPT-3’s ability to understand context makes it able to create highly personalized experiences based on user input without requiring complex programming knowledge from developers building applications using this technology.

    In February 2023, Microsoft launched Bing AI and the New Edge browser that uses OpenAI’s GPT-4 language model to access the web and generate responses. The Bing Chat (Bing AI), can be accessed on the Microsoft Edge browser, however, it is not yet available to everyone.


    Google’s Bard Vs. Microsoft’s Bing Chat: The Clash of Titans
    Both Google’s Bard and Microsoft’s Bing Chat are performing well. Bard hasn’t been yet launched here in India; however, you can use Bing Chat.


    Adobe

    Company Adobe
    Founders John Warnock and Charles Geschke
    Founded December 1982
    Headquarters San Jose, California, U.S
    Top AI Generative Companies - Adobe
    Top AI Generative Companies – Adobe

    You might already be familiar with Adobe and even used some of their products like Adobe Photoshop, Acrobat, Premier Pro, etc.

    When it comes to generative AI, Adobe leverages generative AI within its creative software suite to empower artists and designers. Their generative tools allow users to generate, manipulate, and enhance images, videos, and designs using AI-powered algorithms. This includes features like content-aware fill, intelligent upscaling, and automatic image editing suggestions.

    Intel

    Company Intel
    Founders Gordon Moore and Robert Noyce
    Founded July 18, 1968
    Headquarters Santa Clara, California, U.S.
    Top AI Generative Companies - Intel
    Top AI Generative Companies – Intel

    Intel is well-positioned to lead the way in the development and adoption of generative AI and also working on several other generative AI technologies including the Nervana Neural Network Processor (NNPP), which is a custom-designed processor for deep learning applications. It is designed to accelerate the training and inference of neural networks, making it ideal for generative AI applications. It also developed OpenVINO Toolkit, a software development kit that makes it easy to develop and deploy deep learning applications on Intel hardware. While Nervana provides specialized hardware and software optimizations for efficient training and inference of generative models, OpenVINO offers a unified toolkit for optimizing and deploying these models across diverse Intel hardware platforms.

    Intel has an AI-dedicated arm namely Intel AI Lab, which is a research lab that is focused on developing new generative AI technologies. The Intel AI Lab has developed several generative AI technologies that include Generative Adversarial Networks (GANs, Transformers, and Neural Machine Translation (NMT). The research output from Intel Labs contributes to Intel’s product roadmap and strategy, influencing the development of future Intel processors, platforms, and technologies. Intel is committed to making generative AI accessible to everyone.

    Writesonic

    Company Writesonic
    Founder Samanyou Garg
    Founded October 2020
    Headquarters San Francisco, California, United States
    Top AI Generative Companies - Writesonic
    Top AI Generative Companies – Writesonic

    Writesonic is a company that develops AI writing tools. The company was founded in 2021, headquartered in Austin, Texas. It offers a variety of AI writing tools, including Jasper AI, a large language model that can produce text, translate languages, write a diverse set of creative content, and answer questions in an informative, essay kinda way when prompted.

    It is a rapidly growing company. In 2022, the company raised $125 million in a Series A funding round led by Insight Partners.

    In the AI writing space, the company’s tools are used by businesses and individuals around the world to create high-quality copy, headlines, slogans, captions, and other content faster.

    NVIDIA

    Company NVIDIA
    Founders Jen-Hsun Huang, Curtis Priem, and Christopher Malachowsky
    Founded April 5, 1993
    Headquarters Santa Clara, California, U.S.
    Top 10 AI Generative Companies - NVIDIA
    Top AI Generative Companies – NVIDIA

    NVIDIA is a leading manufacturer of graphics processing units (GPUs) and has made significant contributions to generative AI, particularly through its work on generative adversarial networks (GANs). GANs are composed of two neural networks: a generator network and a discriminator network that compete with each other during training. NVIDIA’s research in this area has resulted in advancements such as image synthesis, style transfer, super-resolution, etc.

    Furthermore, NVIDIA’s Megatron-Turing NLG is an LLM that can generate text from large datasets of code or text; it can also be used for language translation or creative writing tasks. Additionally, they have developed Jarvis – an AI conversational chatbot powered by Megatron-Turing NLG which enables natural conversations between humans and machines. This technology could be applied to many areas such as customer service support or education where communication between people would benefit from the use of natural language processing tools like those provided by NVIDIA’s products.

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    Conclusion

    The advances in generative AI have enabled them to develop powerful tools that facilitate human interaction with computers using natural language processing techniques.

    Overall, these advancements from the above-mentioned companies demonstrate how far generative artificial intelligence technology has come since its inception, and how much potential there remains within this field going forward. Please note that the generative AI landscape is rapidly evolving, and new companies might emerge or gain prominence over the next few months or years. This list of companies is not exhaustive and based upon personal research into their products and research work toward the development of AI and deep learning.

    FAQs

    What is generative AI?

    Generative AI is a type of artificial intelligence that focuses on generating new data that is similar to existing data. This is typically done using deep learning algorithms such as generative adversarial networks (GANs) or variational autoencoders (VAEs).

    What is the latest product launched by OpenAI?

    In 2023, OpenAI launched its latest product, the ChatGPT Plus, based on its GPT-4 LLM.

    What is the latest generative AI Chatbot of Google?

    In 2023, Google launched its generative AI chatbot Bard which it still calls an experiment.

    What does Writesonic do?

    Writesonic is a company that develops AI writing tools. It offers a variety of AI writing tools, including Jasper AI, a large language model that can produce text, translate languages, write a diverse set of creative content, and answer questions in an informative, essay kind of way when prompted.