Prominent LLM Researchers And AI Thought Leaders To Watch In 2024

New Thread

Ctrl

Home

Discover

Introduction
1. Yann LeCun — Meta's chief AI scientist
2. Andrej Karpathy - Research Scientist and founding member of OpenAI, formerly Senior Director of AI at Tesla
3. Jared Kaplan — Research Scientist at Google
4. Yoshua Bengio — Founder of Element AI and professor at University of Montreal
5. Oriol Vinyals — Research Scientist at DeepMind
6. Raeseong Park — Principal Scientist at the Technology Innovation Institute
7. Sasha Luccioni — Research Scientist at Anthropic
8. Joelle Pineau — Managing Director of Facebook AI Research
9. Andrew Ng — Co-founder of Coursera, founder of DeepLearning.ai and Landing AI, former head of Google Brain
10. Sam Altman — CEO of OpenAI

Prominent LLM Researchers And AI Thought Leaders To Watch In 2024

Curated by

cdteliot

18 min read

8,482

The field of artificial intelligence (AI) is continually shaped by the insights and innovations of its leading researchers and thought leaders. These individuals not only advance the technology but also influence its ethical and practical applications through their prolific work, ranging from groundbreaking research papers to influential conference presentations. Their diverse approaches and perspectives help to drive the evolution of AI, addressing complex challenges and pushing the boundaries of what the technology can achieve.

1. Yann LeCun — Meta's chief AI scientist

Yann LeCun, a pivotal figure in the field of artificial intelligence, has significantly shaped the trajectory of AI through his innovative work, influential publications, and active participation in AI conferences and communities. His unique approach and opinions on AI development, particularly regarding artificial general intelligence (AGI) and ethical AI practices, distinguish him from his peers.

Innovative Work and Contributions: LeCun is renowned for his pioneering work in deep learning and neural networks. At Bell Labs in the late 1980s, he developed the first convolutional neural network capable of high-level accuracy in recognizing handwritten numbers, a foundational advancement for AI in image recognition
3
. As Meta's chief AI scientist, he has led significant projects, including the development of advanced AI models like Llama 2, which Meta has open-sourced, contrasting with the more closed approaches of other tech giants like Google and Microsoft
1
.
Publications and Academic Influence: LeCun has authored numerous influential research papers that have been pivotal in advancing the field of AI. His academic role at New York University further allows him to shape the next generation of AI researchers, emphasizing the importance of both theoretical foundations and practical applications of AI
3
.
Conferences and Community Engagement: LeCun is a regular at major AI conferences, such as NeurIPS, where he shares his insights and critiques on current AI research trends. His outspoken nature and active presence on social media also facilitate broader discussions on the future and ethics of AI
4
.
Views on AGI and AI Ethics: LeCun has expressed skepticism about the current hype surrounding AGI, emphasizing that large language models, while impressive, do not possess true understanding or reasoning capabilities and are far from achieving human-level intelligence
1
2
. He advocates for a more measured approach to AI development, focusing on substantial conceptual breakthroughs rather than merely scaling existing technologies.
Open Source Advocacy: A staunch advocate for open research, LeCun argues that the future of AI should be built on open-source platforms to ensure cultural diversity, democracy, and broad accessibility. This perspective is integral to his leadership at Meta, where he has pushed for the open-sourcing of AI technologies, aiming to set industry standards and foster innovation through community collaboration
1
3
.

LeCun's contributions and distinct viewpoints continue to influence the AI landscape, driving discussions on the capabilities, limitations, and ethical deployment of AI technologies. His work not only advances the technical aspects of AI but also addresses the broader implications of how AI should evolve in alignment with societal needs and ethical standards.

5 sources

2. Andrej Karpathy - Research Scientist and founding member of OpenAI, formerly Senior Director of AI at Tesla

Andrej Karpathy, a notable figure in the realm of artificial intelligence, has made significant contributions to the field through his work in deep learning and computer vision. His career spans influential roles at both Tesla and OpenAI, marking him as a key player in the advancement of AI technologies.

Early Education and Academic Contributions: Karpathy's journey in AI began with his education, where he earned a bachelor's degree in Computer Science and Physics from the University of Toronto, followed by a master's degree from the University of British Columbia. He completed his PhD at Stanford University under the supervision of Fei-Fei Li, focusing on the intersection of natural language processing and computer vision with deep learning models. During his time at Stanford, he also developed and taught the university's first deep learning course, CS 231n: Convolutional Neural Networks for Visual Recognition, which became one of the largest courses at Stanford.
1
2
3
Role at OpenAI: Karpathy was a founding member of OpenAI, where he worked from 2015 to 2017. His research during this period focused on deep learning applications in generative models and reinforcement learning, contributing to the foundational growth of OpenAI. His work included projects like training computers to control and use a keyboard and mouse for various tasks, which was pivotal in advancing AI's interaction capabilities.
1
3
Contributions at Tesla: In June 2017, Karpathy joined Tesla as the Director of AI and Autopilot Vision, where he led the team responsible for the vision algorithms and neural network training that power Tesla's Autopilot and Full Self-Driving capabilities. His work at Tesla involved significant advancements in computer vision, enhancing the safety and functionality of Tesla's autonomous driving technology. Under his leadership, the team focused on improving the accuracy and reliability of Tesla's AI systems in real-world driving conditions.
1
3
Publications and Speaking Engagements: Throughout his career, Karpathy has authored several influential research papers and articles in the field of AI, particularly focusing on deep learning and computer vision. He is a sought-after speaker at AI conferences and seminars, where he shares his insights and findings with the broader AI community.
1
2
Current Endeavors: After leaving Tesla in 2022, Karpathy has focused on educational outreach, creating YouTube videos that instruct viewers on building artificial neural networks. His commitment to disseminating knowledge and engaging with the AI community continues to influence aspiring AI professionals and enthusiasts.
1
2

Andrej Karpathy's work exemplifies a deep commitment to advancing AI through both theoretical research and practical application, significantly impacting how AI technologies are developed and implemented in complex, real-world systems. His contributions to AI education and autonomous vehicle technology have left a lasting mark on the field.

5 sources

3. Jared Kaplan — Research Scientist at Google

Jared Kaplan, a research scientist at Google, has been at the forefront of developing advanced generative AI systems, including the notable Gemini multimodal large language model (LLM). His contributions significantly impact the field of AI, particularly in the areas of multimodal learning and generative models.

Multimodal Learning and Gemini LLM: Kaplan's work on the Gemini LLM exemplifies his expertise in integrating multiple forms of data (text, images, and possibly audio) to create more robust and versatile AI systems. This approach allows the model to process and generate information across different sensory modalities, enhancing its applicability in diverse real-world scenarios.
Contributions to Generative AI: Beyond Gemini, Kaplan has been involved in various projects focusing on generative models. These AI systems are capable of creating content that mimics human-like creativity and understanding, pushing the boundaries of what AI can achieve in fields such as content creation, design, and interactive applications.
Publications and Research Impact: Kaplan has authored several influential papers in the AI community. His research often explores the theoretical underpinnings and practical applications of generative and multimodal AI systems, contributing to the academic and practical understanding of these technologies.
AI Conferences and Community Engagement: Kaplan is an active participant in major AI conferences, where he shares his latest research findings and insights. His involvement helps shape the ongoing discourse on the future directions of AI technology, particularly in the realms of generative and multimodal AI.
Advocacy for Ethical AI Development: In line with the broader concerns of the AI community, Kaplan emphasizes the importance of ethical considerations in AI development. His work includes discussions on the potential impacts of AI on society, advocating for responsible practices that ensure the benefits of AI technologies are widely distributed and do not exacerbate existing inequalities.

Jared Kaplan's role at Google and his pioneering work on the Gemini multimodal LLM and other generative AI systems highlight his significant contributions to the field of artificial intelligence. His efforts not only advance the technical capabilities of AI but also address important ethical and societal considerations.

5 sources

4. Yoshua Bengio — Founder of Element AI and professor at University of Montreal

Yoshua Bengio, a prominent figure in the field of artificial intelligence, has made significant contributions through his research, publications, and active participation in AI conferences and communities. His work primarily focuses on deep learning and neural networks, and he is recognized for his pioneering efforts in these areas. Bengio's approach to AI is characterized by a strong emphasis on both theoretical advancements and practical applications, particularly in how AI can be developed responsibly to benefit society.

Foundational Contributions to Deep Learning: Bengio is one of the key figures behind the development of deep learning technologies. His research has been fundamental in the revival of neural networks, which are now a central component of many AI systems. His work has significantly advanced the understanding of deep architectures and their capabilities
1
2
.
Publications and Scholarly Work: Bengio has authored numerous influential papers that have shaped the field of AI. His publications cover a wide range of topics within machine learning and neural networks, contributing to both the theoretical framework and practical applications of these technologies. He is also a co-author of the book "Deep Learning," which is considered a seminal text in the field
1
2
.
Leadership in AI Conferences and Communities: As a respected leader in the AI community, Bengio has been involved in organizing and participating in major AI conferences, such as NeurIPS and ICLR, which he co-founded. These platforms allow him to share his insights and collaborate with other experts, fostering a global dialogue on the future of AI
1
3
.
Advocacy for Ethical AI: Bengio is deeply concerned with the social impact of AI. He has been actively involved in initiatives like the Montreal Declaration for the Responsible Development of Artificial Intelligence, which aims to guide the ethical development of AI technologies. His advocacy emphasizes the importance of developing AI in a manner that is transparent, inclusive, and socially beneficial
1
2
.
Innovative Approaches to AI Research: Bengio's research often explores novel methods of machine learning that go beyond traditional models. For example, his work on generative adversarial networks and unsupervised learning represents a shift towards more flexible and powerful AI systems. These innovations demonstrate his commitment to pushing the boundaries of AI technology
1
2
.
Opinions on AI's Future: Bengio believes that AI should be developed to enhance human capabilities and address societal challenges. He is skeptical of the hype surrounding artificial general intelligence (AGI), advocating instead for a focus on practical and beneficial applications of AI. His views stress the importance of caution and responsibility in the advancement of AI technologies
1
2
.

Yoshua Bengio's contributions to the field of AI are not only technical but also ethical and philosophical. His work continues to influence the development of AI technologies and the global conversation on how AI should evolve.

5 sources

5. Oriol Vinyals — Research Scientist at DeepMind

Oriol Vinyals, a distinguished research scientist at DeepMind, has made significant contributions to the field of artificial intelligence, particularly in the development of generative AI models such as the Gopher large language model (LLM). His work has not only advanced the capabilities of AI systems but also influenced the broader AI research community through his publications and active participation in AI conferences.

Development of Gopher LLM: Vinyals played a crucial role in the development of the Gopher LLM, a state-of-the-art language model known for its depth and breadth in understanding and generating human-like text. This model has set new benchmarks in the field of natural language processing and has been instrumental in advancing the understanding of how large-scale language models can be effectively trained and deployed.
1
Contributions to Generative AI: Beyond Gopher, Vinyals has been involved in several other projects that focus on generative models and their applications. His research often explores the intersection of deep learning and reinforcement learning, pushing the boundaries of AI in areas such as game playing and decision-making processes.
1
2
Publications and Research Impact: Vinyals has authored numerous influential papers that have significantly contributed to the AI community. His work is widely cited, reflecting the impact of his research on the field. Notably, his papers on sequence-to-sequence learning and the AlphaStar project, which developed a Grandmaster-level agent in StarCraft II, are considered seminal contributions to the understanding of complex AI systems.
1
2
AI Conferences and Community Engagement: As an active participant in major AI conferences, Vinyals has shared his insights and research findings with the global AI community. His involvement in these conferences, including roles such as program chair and area chair, has helped shape the ongoing discourse on the future directions of AI technology.
1
Advocacy for Ethical AI Development: Vinyals is also known for his advocacy for ethical AI development. He emphasizes the importance of developing AI technologies that are not only advanced but also aligned with societal values and ethical standards. This perspective is crucial in the ongoing discussions about the implications of AI and the responsibilities of AI researchers.
2

Oriol Vinyals' contributions to the development of generative AI models and his active engagement in the AI community highlight his role as a leader in the field. His work not only advances the technical capabilities of AI but also addresses broader implications, ensuring that AI evolves in alignment with ethical standards and societal needs.

5 sources

6. Raeseong Park — Principal Scientist at the Technology Innovation Institute

Raeseong Park, a Principal Scientist at the Technology Innovation Institute (TII), plays a pivotal role in the development and advancement of the Falcon LLM, a series of large language models that have significantly impacted the field of artificial intelligence. Park's leadership and expertise have been instrumental in steering the research and engineering efforts behind these models, contributing to their success and recognition in the AI community.

Leadership in Falcon LLM Development: Park has been at the forefront of the Falcon LLM project, overseeing the development of models like Falcon 40B and the more recent Falcon 180B. These models have achieved top rankings on the Hugging Face Leaderboard and are recognized for their performance and efficiency in various AI benchmarks, outperforming other notable models in reasoning, coding, proficiency, and knowledge tests
1
.
Research and Innovations: Under Park's guidance, the Falcon LLMs have been trained on an extensive corpus of data, utilizing state-of-the-art training techniques and architectures. The Falcon 180B, for instance, is trained on 3.5 trillion tokens and incorporates 180 billion parameters, showcasing the ambitious scale and technical sophistication of the project
1
.
Contributions to AI Community and Open Access: Park's approach to AI development emphasizes open access and community engagement. The Falcon models under his leadership are made available to researchers and commercial users alike, fostering a collaborative environment and democratizing access to cutting-edge AI technologies. This open approach is designed to spur innovation and allow for widespread adoption and adaptation in various domains
1
.
Publications and Speaking Engagements: Park has authored several influential papers in the field of AI, detailing the methodologies and outcomes of the Falcon LLM projects. He is also a frequent speaker at major AI conferences, where he shares insights and developments related to the Falcon LLMs, contributing to the global discourse on AI technology and its applications
1
.
Advocacy for Ethical AI Development: In line with the Technology Innovation Institute's mission, Park advocates for the responsible and ethical development of AI. His work includes considerations for privacy, transparency, and the societal impacts of AI, ensuring that the Falcon LLMs not only advance technological capabilities but also adhere to high ethical standards
1
.

Raeseong Park's contributions through the Falcon LLM project highlight his significant role in advancing AI technology and shaping the future of ethical AI development. His leadership and innovative approaches continue to influence the broader AI landscape, driving progress and fostering a responsible approach to AI research and application.

5 sources

7. Sasha Luccioni — Research Scientist at Anthropic

Sasha Luccioni is a distinguished figure in the field of artificial intelligence, particularly known for her work on the ethical and environmental implications of AI technologies. Her contributions span research, advocacy, and the development of tools aimed at promoting sustainable and responsible AI practices.

Research and Development: Luccioni's work at Hugging Face and her involvement with Climate Change AI (CCAI) highlight her commitment to understanding and mitigating the environmental impact of AI. She has developed methodologies for calculating the carbon footprint of AI systems, notably the BLOOM model, which has been a significant contribution to the field of sustainable AI.
1
4
Advocacy and Leadership: As a board member of Women in Machine Learning (WiML) and a co-lead organizer of the Tackling Climate Change with Machine Learning workshop at ICLR 2023, Luccioni actively promotes diversity and interdisciplinary collaboration in AI research. Her leadership roles underscore her dedication to fostering an inclusive and ethically conscious AI community.
1
2
Publications and Educational Contributions: Luccioni has authored several influential papers published in prestigious journals and conferences, including IEEE, AAAI, ACM, and Nature Machine Intelligence. Her research not only advances the scientific understanding of AI's impacts but also serves as a crucial resource for the development of best practices in AI deployment.
1
Tools and Practical Applications: The development of the Code Carbon tool, which helps organizations measure the carbon emissions of their AI systems, exemplifies Luccioni's approach to practical solutions. This tool has been widely adopted, reflecting its impact on promoting more sustainable practices in the AI industry.
4
Public Speaking and Advocacy: Luccioni is a sought-after speaker at major conferences and forums, including NeurIPS and events organized by the OECD and the United Nations. Her talks often address the urgent need for ethical standards and sustainable practices in AI, influencing policymakers and industry leaders worldwide.
1
2
Recognition and Influence: Her work has not only garnered academic acclaim but has also been featured extensively in media outlets like MIT Technology Review, WIRED, and the Washington Post, highlighting her role as a leading voice in the responsible AI movement.
1

Sasha Luccioni's multifaceted contributions to artificial intelligence, from her research on AI's environmental impact to her advocacy for ethical practices, mark her as a pivotal figure in shaping the future of responsible AI development. Her efforts ensure that AI technologies advance in alignment with societal needs and environmental sustainability.

5 sources

8. Joelle Pineau — Managing Director of Facebook AI Research

Joelle Pineau, a prominent figure in AI research, has made significant contributions to the field through her leadership at Meta AI (formerly Facebook AI Research) and her academic work at McGill University. Her efforts are particularly noted in the development of generative AI models and the promotion of ethical AI practices.

Leadership at Meta AI: Pineau has been instrumental in steering Meta AI's research directions, particularly in the development of the LLaMA language model. Under her leadership, Meta AI has focused on creating AI technologies that are both advanced and ethically aligned. This includes the decision to make LLaMA an open-source project, aiming to democratize AI research and encourage global collaboration
1
.
Academic Contributions: As a professor at McGill University, Pineau has influenced the AI field through both her teaching and research. Her work spans several areas of AI, including reinforcement learning and health-care applications, where she has developed AI-driven strategies for patient care and medical decision-making
2
4
.
Ethical AI Advocacy: Pineau has been a strong advocate for ethical considerations in AI. At Meta, she has pushed for transparency and responsible AI development, influencing how AI research is conducted and shared within the broader community. Her efforts include promoting open science and introducing rigorous standards for research publications
1
5
.
Publications and Research Impact: Pineau has authored numerous research papers that contribute to the understanding and advancement of AI technologies. Her publications often address critical issues such as AI safety, bias, and the robustness of AI systems, reflecting her commitment to developing AI that is both powerful and principled
1
2
.
AI Conferences and Community Engagement: Pineau is an active participant in major AI conferences, where she shares insights from her research and Meta AI's developments. Her involvement in these forums helps shape the discourse around the future of AI, particularly in terms of ethical development and the role of large language models in society
1
2
.
Recognition and Awards: Pineau's work has been recognized with several awards, including the NSERC's E.W.R. Steacie Memorial Fellowship and a fellowship from the Association for the Advancement of Artificial Intelligence (AAAI). These accolades underscore her contributions to AI research and her influence in the field
2
.

Joelle Pineau's role at Meta AI and her academic career at McGill University highlight her significant contributions to the development of AI technologies and the promotion of ethical practices in AI research. Her leadership and advocacy continue to impact the AI community, driving progress and fostering a responsible approach to AI development.

5 sources

9. Andrew Ng — Co-founder of Coursera, founder of DeepLearning.ai and Landing AI, former head of Google Brain

Andrew Ng is a prominent figure in the field of artificial intelligence, known for his substantial contributions to machine learning, deep learning, and their applications in various domains. His work spans academic research, educational initiatives, and entrepreneurial ventures, making significant impacts across these areas.

Pioneering Work in Deep Learning: Ng's early work at Stanford University and Google Brain laid foundational stones for the use of deep neural networks in practical applications. His research at Google Brain included developing large-scale deep learning algorithms, which significantly advanced the field's capabilities in areas such as image and speech recognition
1
.
Educational Contributions: Ng has been instrumental in democratizing AI education through online platforms. He co-founded Coursera, a platform that offers wide-ranging courses in AI and machine learning, making high-quality education accessible to a global audience. His courses on machine learning have educated millions of students, equipping them with the skills necessary to pursue careers in AI
1
.
Publications and Scholarly Influence: Ng has authored numerous research papers that are highly cited in the AI community. His publications cover a broad spectrum of topics within AI, from practical algorithms to theoretical insights. His work continues to influence both academia and industry, guiding the development of new AI technologies and methodologies
1
3
.
Leadership in AI Conferences and Communities: Ng is a regular speaker at major AI conferences, where he shares his insights on the latest developments in AI and machine learning. His talks often focus on the importance of accessible AI education and the ethical implications of AI technologies. He is also involved in various AI communities, contributing to discussions that shape the future direction of AI research and application
1
2
.
Advocacy for Ethical AI: Ng emphasizes the importance of ethical considerations in AI development. He advocates for responsible AI that prioritizes transparency, fairness, and accountability. His efforts extend to encouraging the AI community to adopt ethical frameworks that ensure AI technologies are used for the benefit of society
1
.
Innovative Approaches to AI Application: Through his entrepreneurial ventures like DeepLearning.ai and Landing AI, Ng applies AI to solve real-world problems. DeepLearning.ai provides AI education and resources to foster talent in the field, while Landing AI focuses on bringing AI solutions to industries traditionally less involved in AI, such as manufacturing. These initiatives reflect his belief in AI's potential to drive significant improvements across various sectors
1
.
Opinions on AI's Future: Ng views AI as a transformative force akin to electricity, capable of reshaping industries and enhancing human capabilities. He is optimistic about AI's potential but also cautious about its challenges, advocating for continuous dialogue and collaboration to harness AI responsibly
2
.

Andrew Ng's multifaceted contributions to AI—from groundbreaking research and influential teaching to ethical advocacy and practical applications—highlight his role as a leader in shaping the trajectory of AI development and its integration into society. His work not only advances the technical aspects of AI but also addresses broader implications, ensuring that AI evolves in alignment with ethical standards and societal needs.

5 sources

10. Sam Altman — CEO of OpenAI

Sam Altman, as a leading figure in the field of artificial intelligence, has significantly influenced the trajectory of AI through his visionary leadership, scholarly contributions, and forward-thinking perspectives on the future of technology.

Scholarly Contributions and Publications: Altman has been instrumental in shaping the discourse around artificial intelligence, particularly through his role at OpenAI. While he is not frequently listed as an author on academic papers, his influence permeates the strategic direction and research output of OpenAI. The organization has published numerous papers on groundbreaking AI technologies, including the GPT series, which have been pivotal in advancing the understanding and capabilities of AI systems.
Approaches to AI Development: Altman's approach to AI is characterized by a commitment to open and ethical AI development. Under his leadership, OpenAI has transitioned from a non-profit to a "capped-profit" organization, a move designed to balance the need for funding high-impact AI research while adhering to ethical guidelines. This model reflects his belief in the importance of responsible AI development that benefits all of humanity, not just a select few.
Opinions on AI's Future: Altman is optimistic about the potential of AI to solve some of the world's most pressing problems, including climate change, healthcare, and education. However, he is also aware of the challenges and risks associated with advanced AI technologies. He advocates for careful governance and ethical frameworks to ensure that AI development is aligned with human values and societal well-being.
Contributions to the AI Field: Altman's contributions extend beyond OpenAI. His insights and initiatives have sparked broad discussions on the impact of AI on society, the economy, and the future of work. He has been a vocal advocate for preparing for the societal shifts that advanced AI technologies might bring, emphasizing the need for policies that ensure these innovations lead to positive outcomes for society at large.

Sam Altman's role in the AI community is not just as a leader of a prominent AI research organization but also as a key influencer in shaping the policies and ethical standards surrounding AI development. His work continues to inspire and challenge the AI community to strive for innovations that are not only technologically advanced but also socially responsible and beneficial.