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AI Leaders: List of the Top 10 Visionaries in the Industry

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Yann LeCun


The AI revolution is afoot. Like the steam engine, combustion engine, and computer revolution before it, artificial intelligence will undoubtedly profoundly impact how humans work and live.

One of the most exciting advances in AI development is deep learning, which powers a range of technologies from facial recognition to self-driving cars.

Though many people are familiar with its practical applications, like autonomous vehicles, few understand how deep learning works today. You will want to follow these people on LinkedIn, Twitter, and other social media for true updates in the fascinating updates in AI.

Yann LeCun

Yann LeCun

Yann LeCun is a French computer and cognitive scientist considered one of the pioneers of artificial intelligence. He is the head of the AI research lab at Facebook, overseeing research in artificial intelligence, machine learning, natural language processing, and more. LeCun is also working as a Silver Professor of Computer Science at New York University. Enjoy this YouTube with Yann LeCun.

LeCun has been awarded numerous accolades, including the ACM Turing Award, which he humbly shows on his website, mentioning, ‘sounds like I’m bragging, but a condition of accepting the award is to write it next to your name.’

LeCun’s work has had a profound impact on artificial intelligence as well as other fields of computer science. His contributions include several ground-breaking ideas and creations in fields such as artificial neural networks and vision processing that have shaped our understanding of learning and intelligence today.

Geoffrey Hinton

Geoffrey Hinton
Geoffrey Hinton

Geoffrey Hinton is a world-renowned artificial intelligence researcher and educator with a Ph.D. in AI from the University of Edinburgh. After finishing his degree, he became a research scientist at a Google Brain-based facility. He led a group of engineers to develop deep neural networks and the deep learning revolution. This work has been instrumental in shaping today’s AI landscape. Enjoy this YouTube with Geoffrey Hinton.

One of the breakthroughs in AI and computer vision history is the creation of Alex-Net, an image recognition program designed with the help of his students. Hinton also received the Turing award along with Yoshua Bengio and Yann LeCun. This led to the three of them being called the ‘Godfathers of Deep Learning.’

Hinton is also the founding director of the University of Toronto’s Vector Institute for Artificial Intelligence and the Canada Research Chair in Neural Information Processing Systems. He is a frequent speaker on AI topics, often giving keynote speeches and participating in panel discussions. While his contributions to the field are undeniable, it’s worth noting that they’re limited to academia.

Kate Crawford

Kate Crawford
Kate Crawford

Kate Crawford currently works at Microsoft as a senior principal researcher. She also works as a visiting professor at the MIT Center for Civic Media. She has a background in cultural and media studies and has published widely on the social and cultural impacts of big data, machine learning, and AI. She’s also a founding member of the AI Now Institute and served as its co-director. Enjoy this YouTube with Kate Crawford.

Her main contribution to the field of AI is her critical perspective on the social implications of technology and how it can perpetuate existing power structures and biases. Through her writing, research, and public speaking, Crawford has helped to bring attention to important ethical and policy questions surrounding AI. He has advocated for more responsible and equitable development and deployment of the technology.

Demis Hassabis

Demis Hassabis
Demis Hassabis

Demis Hassabis is a co-founder and CEO of DeepMind, an AI company focusing on neuroscience. Google later bought the company in the year 2014. Enjoy this YouTube with Demis Hassabis.

Hassabis has a Ph.D. in cognitive neuroscience from University College London and has worked on deep reinforcement learning and game AI, leading to AlphaGo, the first AI to defeat a world champion in Go.

Demis himself was a gaming enthusiast, and right after graduating in computer sciences, he founded Elixir Studios, a pioneering video games company. His interest in gaming led him to develop the game ai.

Moreover, Hassabis is among the leaders in ai because of his work in autobiographical memory and amnesia which led him to author several academic papers that heavily influenced the ai field.

Fei-Fei Li

Fei-Fei Li
Fei-Fei Li

Dr. Fei-Fei Li is a computer scientist, artificial intelligence expert, and entrepreneur. She holds a Ph.D. in Electrical Engineering from the California Institute of Technology and a BS in Computer Science from Princeton University, both with honors. Enjoy this YouTube with Dr. Fei-Fei Li.

She was a professor at Stanford University before joining Google in 2017 as the Vice President of Google and Chief Scientist of Google Cloud AI/ML. Dr. Li has led teams developing vision and machine learning for large-scale image and video recognition creating ImageNet, a massive database of annotated images that has become a benchmark for computer vision algorithms. Her research has had a major impact on fields from computer vision to artificial intelligence.

Leading global tech companies such as Google and Facebook have recognized Dr. Fei-Fei’s work and appointed her a distinguished scientist. Dr. Li has been instrumental in shaping AI research through her contributions to machine learning and vision. Her years of experience have made her a leading voice on AI development within tech giants and governments worldwide.

Ian Goodfellow

Ian Goodfellow
Ian Goodfellow

Ian Goodfellow works at Deep Mind and was previously Apple’s Machine Learning department director. He did Ph.D. in machine learning from the University of Montreal and has published numerous research papers in top-tier conferences and journals. Enjoy this YouTube with Ian Goodfellow.

Some of his notable achievements include being the lead author of the textbook “Deep Learning” and co-inventing the generative adversarial network (GAN) framework, which has become one of the top-used techniques in deep learning.

Goodfellow’s main contribution to the field of AI is his pioneering work on deep learning and developing the GAN framework. Through his research and writing, he has helped to advance the field and popularize deep learning, leading to several breakthroughs in computer vision, natural language processing, and other domains. He is also a well-known and respected figure in the AI community and has helped to foster greater collaboration and exchange of ideas between researchers, practitioners, and policymakers.

Kai-Fu Lee

Kai-Fu Lee
Kai-Fu Lee

Kai-Fu Lee is a tech thought leader with a Ph.D. in Computer Science. He has worked as a founding director at Microsoft Asia, former president at Google china, and the CEO at Sinovation Ventures (a venture capital firm). Enjoy this YouTube with Kai-Fu Lee.

His areas of expertise include artificial intelligence and machine learning, speech recognition, and the impact of AI on society and the global economy. As a thought leader, he’s made significant contributions to the growth of AI and its impact on society.

A prominent scholar, Dr. Lee has been a global keynote speaker at numerous tech conferences, including TED. Anyone looking to read about the growth of AI and tech in China should read his book ai Superpowers: China, Silicon Valley, and the New World Order. With his experience in the tech industry, Dr. Lee is an influential voice in the discussion surrounding AI and its role in the future of technology. His work has helped shape the advancements made in the area of AI over the years

Ilya Sutskever

Ilya Sutskever
Ilya Sutskever

Ilya Sutskever is a co-founder of OpenAI, a non-profit AI research company. He has made several significant contributions in the deep learning field, including establishing AlexNet, a CNN (Convolutional Neural Network), and Geoffrey Hinton and Alex Krizhevsky. Enjoy this YouTube with Ilya Sutskever.

Sutskever has also worked as a research scientist at Google Brain, where he worked with Quoc Le and Oriol Vinyals to program sequence-to-sequence learning algorithms.

As a researcher and leader, Sutskever has made significant contributions to AI research that have had a major impact on current fields, the current ChatGPT, and the establishment of all AI-based tools powered by Openai.

Andrew Ng

Andrew Ng
Andrew Ng

Andrew “Geoff” Ng is a co-founder of Google Brain, an Alphabet Inc. division focusing on artificial intelligence and machine learning. He also worked as the chief scientist at Baidu Inc., where he established the AI sector of the company. Enjoy this YouTube with Geoff Ng.

Currently, Andrew Ng is serving as the CEO of Landing AI, which supports developers with limited datasets to take their projects from proof-of-concept to full-fledged production.

As a leader in machine learning, especially in developing large-scale online learning algorithms, Ng has played a critical role in defining the future of AI. His efforts have opened up numerous possibilities for both research and industry to address challenges that stem from AI.

His efforts have also helped expand access to AI education and research opportunities for individuals worldwide.

Mustafa Suleyman

Mustafa Suleyman
Mustafa Suleyman

Mustafa Suleyman is a co-founder of DeepMind, an AI company acquired by Google in 2014. Suleyman has a background in computer science and has been at the top of the development and deployment of AI technologies for over a decade. Enjoy this YouTube with Mustafa Suleyman.

Some of his notable achievements include leading the team at DeepMind that developed AlphaGo, the first AI program to defeat a world champion in the game of Go. He was also instrumental in developing DeepMind’s reinforcement learning techniques, which have been applied to various real-world problems, including energy efficiency and protein folding.

Suleyman’s main contribution to the field of AI is advancing the capabilities of artificial intelligence, particularly in reinforcement learning and deep learning. He has been voicing opinions about the responsible development and deployment of AI technologies.

Parting Words:

AI has a promising future ahead of it. AI is already providing us with AI-powered solutions and transforming how we work and live. Our list of professionals in the field of AI can show us the way to hear and learn about the deep work of AI and the deep learning that can take place in each person’s life.

AI is a technology that requires a collaborative effort from various tech, science, and business experts to move forward. The future is exciting, and we are here now. We can follow the leading AI thinkers of our time; the time has never been greater in the history of the world — and we can all take advantage of this AI phenomenon.

The leaders mentioned above are among the foremost visionaries in the world today — setting examples for AI development.

Inner Image Photos: Most taken from these Professional Linkedin.com photos; Thank you!
Featured Image Credit: Photo by Henri Mathieu-Saint-Laurent; Pexels Thank you!

Brad Anderson

Brad Anderson

Editor In Chief at ReadWrite

Brad is the editor overseeing contributed content at ReadWrite.com. He previously worked as an editor at PayPal and Crunchbase. You can reach him at brad at readwrite.com.



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Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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