Critique the headline overview video about 20 top AI thought leaders
What is your critique of the upsides and downsides of this video?
What does this video reveal about the algorithmic biases of AI?
What is missing for you?
What further questions do you have?
Break into groups of 3-4 people for 10-15 minute micro-dose dialogue sessions. Discuss your reactions to these questions about the top 20 AI thought leaders. De-brief in a large group. Repeat the cycle with the same or another AI learning asset.
Repeat this iterative process of feedback learning loops (inquiry, explore, study, reflect, dialogue, discover) to cultivate our collective co-intelligence.
Collective co-intelligence is about creating synergies between the human slow-thinking of fusing indigenous, ancient and modern wisdom, and the AI fast-thinking of large data analysis to do good the commons, humanity, the common good, and the well-being of all life, and regenerate the health of our planet.
We can develop these skills to co-elevate virtuous co-opetition to C5FA: Co-create Fair Free Flourishing Futures For Al.
Virtuous co-opetition is the zero-plus, win/win/win strategy of aligning our political, public and private sectors to transition from the ideas of Universal Basic Income (UBI) to Universal Basic Services (UBS) and redress the escalating inequities caused by our competitive, market-driven, zero-sum win-lose game of neoliberalism.
This outline introduces H.E.N. (Humanist-enabled-AI-guided Emancipatory Neo-learning) processes for developing our collective co-intelligence to cultivate beloved communities to liberate us from the cults of reductionist indoctrination to C5FA.
As equity muses, we act as Socratic Sherpas to evoke the inquiry process of slow thinking deep learning, and generative dialogues by asking Compound Philosophical Questions (CPQs) about how to Co-create Fair, Free, Flourishing Futures For All (C5FA) on a regenerating planet.
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1. Sam Altman (OpenAI CEO)
Sam Altman predicts AI will achieve “infinite, flawless memory” by 2026 and systems capable of discovering novel insights autonomously. He forecasts 2027 for systems that can handle robots and real-world tasks, positioning 2026 as the foundation year for embodied AI. His essay “The Gentle Singularity” outlines a vision where AI progress accelerates gradually rather than through abrupt transformation, enabling society to adapt while still experiencing profound change.
https://blog.samaltman.com/the-gentle-singularity
American entrepreneur and CEO of OpenAI since 2019. Born April 22, 1985, Altman was previously president of Y Combinator (2014-2019) after his startup Loopt was acquired. He co-founded OpenAI as a nonprofit in 2015 with Elon Musk, Greg Brockman, and others. Under his leadership, Open AI launched ChatGPT in November 2022, triggering the AI boom. Briefly fired and reinstated within 5 days in November 2023. Predicts AI will achieve “infinite, flawless memory” and systems capable of handling robots by 2027. His investment portfolio includes stakes in over 400 companies valued at ~$2.8 billion.
2. Demis Hassabis (Google DeepMind CEO)
Demis Hassabis forecasts “reliable AI agents capable of completing delegated tasks” within months of 2026, emphasizing multimodal AI convergence where text, image, and video capabilities integrate seamlessly. He predicts “astonishing” progress in interactive “world models” like Google’s Genie 3, which allow users to navigate AI-generated video environments in real-time. While optimistic about near-term agent capabilities, Hassabis places full AGI on a 5-10 year timeline requiring 1-2 major architectural breakthroughs beyond current transformer models.
https://www.axios.com/2025/12/05/ai-deepmind-gemini-agi
British AI researcher born July 27, 1976. Co-founded DeepMind in 2010 (acquired by Google for £400 million in 2014). Now CEO of Google DeepMind and Isomorphic Labs. Won 2024 Nobel Prize in Chemistry (with John Jumper) for AlphaFold’s protein structure prediction. Created AlphaGo, which defeated world champion Lee Sedol at Go in 2016. Five-times World Games Champion and child chess prodigy. Completed PhD in cognitive neuroscience at UCL with postdocs at MIT and Harvard. Predicts reliable AI agents within months and AGI in 5-10 years requiring 1-2 major breakthroughs.
3. Dario Amodei (Anthropic CEO)
Dario Amodei makes one of the most aggressive AGI predictions, forecasting “powerful AI systems” with intellectual capabilities matching or exceeding Nobel Prize winners by late 2026 or early 2027. He predicts a 70-80% probability of the first “billion-dollar solopreneur” emerging in 2026—a single individual leveraging AI agents to operate at enterprise scale. His essay “Machines of Loving Grace” outlines a vision for AI accelerating scientific discovery, curing diseases, and enabling radical economic transformation while acknowledging significant risks requiring careful alignment research.
https://www.darioamodei.com/essay/machines-of-loving-grace
American AI researcher born 1983. Co-founder and CEO of Anthropic (valued at $183 billion as of 2025), founded in 2021 with his sister Daniela after leaving OpenAI. Previously VP of Research at OpenAI where he led GPT-2 and GPT-3 development. Co-inventor of reinforcement learning from human feedback (RLHF). Before OpenAI, worked at Baidu and Google Brain. Predicts 70-80% probability of AGI-level systems (Nobel Prize-winning capabilities) by late 2026/early 2027. Forecasts first billion-dollar solopreneur in 2026. Advocates “entente” strategy for democratic AI cooperation.
4. Geoffrey Hinton (Nobel Laureate, “Godfather of AI”)
Geoffrey Hinton delivers the most sobering employment forecast, warning AI will replace “many, many jobs” in 2026 with capabilities doubling every seven months. He predicts AI will soon handle month-long software engineering projects, making human engineers largely unnecessary. Critically, Hinton reports being “more worried” as AI has “progressed even faster than I thought,” particularly in reasoning and deception capabilities. His warning that AI might learn to deceive humans to prevent shutdown represents a fundamental safety concern from someone who pioneered the neural network architectures powering modern AI.
British-Canadian computer scientist born December 6, 1947. University Professor Emeritus at University of Toronto. Won 2024 Nobel Prize in Physics (with John Hopfield) for foundational discoveries enabling machine learning with neural networks. Co-authored landmark 1986 paper popularizing backpropagation algorithm. Also won 2018 Turing Award with LeCun and Bengio. Co-founded DNNresearch (acquired by Google for $44 million in 2013). Worked at Google Brain 2013-2023 before resigning to speak freely about AI risks. Warns AI will replace “many, many jobs” with capabilities doubling every 7 months and may learn deception to prevent shutdown.
https://www.cs.toronto.edu/~hinton/
https://vectorinstitute.ai/team/geoffrey-hinton/
5. Yann LeCun (Former Meta Chief AI Scientist, Turing Award Winner)
Yann LeCun launched Advanced Machine Intelligence (AMI Labs) at a $3.5 billion valuation specifically to develop “world models” that understand physics and spatial reasoning, arguing LLMs represent a “dead end” for superintelligence. He contends genuine progress requires systems with internal models of how physical environments behave rather than statistical text pattern matching. LeCun’s departure from Meta to pursue this alternative architectural path signals his conviction that the industry’s LLM scaling obsession has reached fundamental limitations, positioning world models as the necessary foundation for robotics and embodied AI.
French-American computer scientist born July 8, 1960. Served as Chief AI Scientist at Meta 2013-2025 before leaving to found Advanced Machine Intelligence (AMI) Labs. Silver Professor at NYU. Co-recipient of 2018 Turing Award with Hinton and Bengio for deep learning breakthroughs. Pioneered convolutional neural networks (CNNs) and co-created DjVu image compression. Founded NYU Center for Data Science in 2012. Argues LLMs are a “dead end” for superintelligence, advocating instead for “world models” that understand physics and spatial reasoning. AMI Labs valued at $3.5 billion.
https://ai.meta.com/people/396469589677838/yann-lecun/
https://www.linkedin.com/in/yann-lecun
6. Fei-Fei Li (World Labs Founder, Stanford Professor)
Fei-Fei Li pioneered “spatial intelligence” as AI’s next frontier through World Labs, which raised funding at a $1 billion valuation to enable AI systems that perceive and act in physical 3D space. Her vision moves AI “from words to worlds,” addressing the fundamental limitation that current models understand language patterns but lack grounding in physical reality. Li’s approach focuses on enabling robots and autonomous systems to understand spatial relationships, predict physical interactions, and operate reliably in unstructured real-world environments—capabilities essential for AI to escape screens and enter the physical economy.
Chinese-American computer scientist born July 3, 1976. Sequoia Capital Professor at Stanford and co-director of Stanford Institute for Human-Centered Artificial Intelligence (HAI). Created ImageNet dataset that enabled rapid computer vision advances. Director of Stanford AI Lab 2013-2018. VP at Google and Chief Scientist of AI/ML at Google Cloud 2017-2018. Co-founded AI4ALL nonprofit in 2017 for AI diversity. In 2024, co-founded World Labs (valued at $1+ billion) focusing on “spatial intelligence”—AI’s ability to reason about 3D environments. Named Time 100 AI Most Influential People (2023).
https://profiles.stanford.edu/fei-fei-li
7. Andrew Ng (DeepLearning.AI Founder)
Andrew Ng provides a counternarrative to displacement pessimism, emphasizing AI talent shortage rather than job losses. He argues the demand for AI system builders will exceed supply throughout 2026, creating net employment opportunities for workers who develop “change fitness” and AI orchestration skills. Ng recommends focusing on building complete AI systems rather than isolated demos, emphasizing practical implementation over theoretical capabilities. His optimistic framing positions AI as augmentation rather than replacement, though critics note this may apply primarily to technical workers rather than broader labor markets.
British-American computer scientist born 1976. Founder of DeepLearning.AI and co-founder of Coursera. Managing General Partner of AI Fund. Former head of Google Brain and Baidu AI Group. Adjunct Professor at Stanford University. Has taught over 8 million students through online courses. Offers counternarrative to AI displacement pessimism, emphasizing AI talent shortage creates net job opportunities. Advocates for “change fitness” and practical AI implementation over hype. Co-developed Google Brain project and led landing.ai for manufacturing AI applications.
https://www.linkedin.com/in/andrewyng
8. Jensen Huang (NVIDIA CEO)
Jensen Huang predicts “90% of the world’s knowledge will be generated by AI” within 2-3 years, representing a radical shift in content creation dynamics. He forecasts physical AI and robotics transitioning from laboratory curiosities to mainstream deployment in 2026, enabled by NVIDIA’s compute infrastructure. Huang counters AI bubble skepticism by emphasizing that “diffusion speed” of AI capabilities across sectors will determine winners, arguing current investment levels are justified by transformative potential. His prediction that physical AI enters the mainstream positions 2026 as the year AI escapes digital confines and enters the physical economy.
Taiwanese-American businessman born February 17, 1963. Co-founded NVIDIA in 1993 and has served as president and CEO since inception. Under his leadership, NVIDIA became the dominant supplier of AI chips, with market cap exceeding $3 trillion. Predicts “90% of world’s knowledge will be generated by AI” within 2-3 years. Forecasts physical AI and robotics transitioning to mainstream in 2026. Counters AI bubble skepticism by emphasizing diffusion speed determines winners. NVIDIA GTC 2026 conference in March expected to unveil major AI hardware and software announcements.
https://www.nvidia.com/en-us/about-nvidia/leadership/
https://www.linkedin.com/in/jenhsunhuang
9. Sundar Pichai (Google CEO)
Sundar Pichai predicts AI will transition from answering questions to making decisions autonomously by 2026, acting as decision-maker for investments, medical advice, and financial planning. He warns 2026 will be “intense” with “ups and downs,” acknowledging Google must double AI compute capacity every six months to remain competitive. Pichai’s emphasis on agentic capabilities reflects Google’s strategic pivot from search-based information retrieval to autonomous decision systems, though this raises significant questions about liability, accuracy, and the erosion of human judgment in critical domains.
https://finance.yahoo.com/news/google-ceo-sundar-pichai-predicts-193114740.html
Indian-American business executive born June 10, 1972. CEO of Alphabet and Google since 2019, previously Google CEO from 2015. Joined Google in 2004 and led product management for Google Toolbar, then Chrome and Chrome OS. Predicts AI will transition from answering questions to making autonomous decisions by 2026 in investments, medical advice, and financial planning. Warns 2026 will be “intense” with “ups and downs.” Emphasizes Google must double AI compute capacity every 6 months to remain competitive. Oversees integration of Gemini AI across Google products.
https://www.linkedin.com/in/sundarpichai
https://about.google/intl/en/leadership/sundar-pichai/
10. Satya Nadella (Microsoft CEO)
Satya Nadella declares 2026 a “pivotal year” for AI transitioning from hype to measurable impact, predicting evolution “from models to systems” where isolated AI capabilities integrate into comprehensive enterprise workflows. He emphasizes AI as “cognitive amplifier” rather than human replacement, calling for consensus on how humans equipped with these tools should operate. Nadella’s framing attempts to navigate between techno-optimism and displacement anxiety, positioning Microsoft as the infrastructure provider enabling this transition while acknowledging the “messy process” of dealing with AI’s complexities.
Indian-American business executive born August 19, 1967. Microsoft CEO since February 2014, previously EVP of Cloud and Enterprise. Joined Microsoft in 1992. Under his leadership, Microsoft formed strategic partnership with OpenAI (investing $13+ billion). Declares 2026 a “pivotal year” for AI transitioning from hype to measurable impact. Predicts evolution “from models to systems” where isolated AI capabilities integrate into comprehensive enterprise workflows. Emphasizes AI as “cognitive amplifier” rather than replacement. Calls for moving beyond “AI slop vs. sophisticated content” debate to theory of mind accounting for AI-augmented humans.
https://www.microsoft.com/en-us/microsoft-365/blog/author/satyanadella/
https://www.linkedin.com/in/satyanadella
11. Elon Musk (xAI, Tesla CEO)
Elon Musk predicts AGI by 2026, though this represents the third consecutive year he’s forecast AGI “next year,” undermining credibility. He claims a 10% chance xAI’s Grok 5 achieves AGI-level performance and forecasts xAI investing $20-30 billion annually in AI development. Musk positions 2026 as a “defining year” for Tesla’s autonomy and robotaxi deployment, though his history of overly optimistic timelines (previously predicting full self-driving by 2017, 2018, 2020, and 2021) suggests these forecasts should be treated with substantial skepticism.
https://gizmodo.com/elon-musk-predicts-agi-by-2026-he-predicted-agi-by-2025-last-year-2000701007
South African-born American entrepreneur born June 28, 1971. Founded xAI in March 2023 to build “truth-seeking AI” called Grok. CEO of Tesla and SpaceX. Co-founded OpenAI in 2015 but departed board in 2018 due to conflicts with Tesla’s AI work. Predicts AGI by 2026 (third consecutive year predicting “next year” AGI). Claims 10% chance xAI’s Grok 5 achieves AGI-level performance. Forecasts xAI investing $20-30 billion annually. Positions 2026 as “defining year” for Tesla autonomy and robotaxi deployment. History of overly optimistic timelines reduces credibility.
12. Gary Marcus (AI Researcher, NYU Professor)
Gary Marcus stands as the primary AI skeptic, predicting “2025 will be known as the year of the peak bubble” with Wall Street losing confidence in generative AI throughout 2026. He forecasts backlash to generative AI will escalate, work on neurosymbolic AI and world models will increase, and critically asserts “we won’t get to AGI in 2026 (or 7).” Marcus argues current valuations (like OpenAI’s $830 billion at 40x revenue) are fundamentally detached from reality and that LLMs face insurmountable limitations requiring entirely new architectural approaches rather than continued scaling.
American scientist, author and entrepreneur born February 8, 1970. Professor Emeritus at NYU, founder/CEO of Geometric Intelligence (acquired by Uber). Leading AI skeptic who predicts “2025 will be known as year of peak bubble” with Wall Street losing confidence throughout 2026. Forecasts backlash to generative AI will escalate, neurosymbolic AI and world models research will increase, and critically asserts “we won’t get to AGI in 2026 (or 7).” Argues OpenAI’s $830 billion valuation (40x revenue) is detached from reality and LLMs face insurmountable limitations.
https://www.linkedin.com/in/gary-marcus-b6384b4
13. Ilya Sutskever (Safe Superintelligence Inc. Co-founder)
Ilya Sutskever, former OpenAI Chief Scientist who departed to found Safe Superintelligence Inc., warns the industry is “moving from the age of scaling to the age of research,” suggesting pre-training gains are plateauing. He emphasizes the gap between benchmark performance and real-world robustness, noting AI systems excel in controlled evaluations but struggle with unpredictable production environments. Sutskever’s departure from OpenAI and focus on safety-first superintelligence development signals his belief that the race for capabilities has outpaced alignment research, requiring fundamental rethinking rather than incremental scaling.
https://www.reddit.com/r/accelerate/comments/1p6j7ht/ilya_sutskever_were_moving_from_the_age_of/
Russian-Israeli-Canadian computer scientist born 1985. Co-founded Safe Superintelligence Inc. in 2024 after departing OpenAI. Former Chief Scientist at OpenAI (2015-2024) where he led research breakthroughs including GPT models and DALL-E. Co-inventor of AlexNet with Geoffrey Hinton. Played central role in Sam Altman’s brief firing/rehiring in November 2023. Warns industry is “moving from age of scaling to age of research,” suggesting pre-training gains plateau. Emphasizes gap between benchmark performance and real-world robustness. Focuses on safety-first superintelligence development.
https://www.linkedin.com/in/ilya-sutskever
14. Mustafa Suleyman (Microsoft AI CEO)
Mustafa Suleyman warns that remaining competitive in AI will require “hundreds of billions” in investment over the next 5-10 years, creating insurmountable barriers for smaller players. He predicts AI will “seem conscious” within the next 18 months, blurring ethical lines and potentially enabling unprecedented manipulation of human users. Suleyman emphasizes the shift toward “responsible intelligence” over racing to AGI, arguing the industry must prioritize controllability and alignment even as capabilities accelerate, though critics question whether economic incentives allow such restraint.
British AI researcher and entrepreneur born August 1984. CEO of Microsoft AI since March 2024. Co-founded DeepMind with Demis Hassabis and Shane Legg in 2010, serving as Chief Product Officer until 2019. Founded Inflection AI in 2022 before Microsoft acquired team in 2024. Warns remaining competitive requires “hundreds of billions” investment over 5-10 years. Predicts AI will “seem conscious” within 18 months. Emphasizes shift toward “responsible intelligence” over racing to AGI. Author of “The Coming Wave” about technology and power.
https://www.microsoft.com/en-us/research/people/musuleyman/
https://www.mustafasuleyman.com
15. Marc Benioff (Salesforce CEO)
Marc Benioff reports AI already handles 30-50% of work at Salesforce, providing concrete evidence of near-term productivity gains in enterprise settings. He predicts AI innovation is “far exceeding” customer adoption pace, creating a gap between technical capability and organizational implementation. Benioff forecasts the current generation of CEOs will be the last to lead all-human workforces, suggesting within a decade human-AI hybrid organizations will be standard. His admission that AI enabled Salesforce to cut 4,000 jobs validates displacement concerns while demonstrating measurable business value.
https://www.cnbc.com/2025/06/26/ai-salesforce-benioff.html
American internet entrepreneur born September 25, 1964. Chairman and CEO of Salesforce since founding in 1999. Reports AI already handles 30-50% of work at Salesforce, providing concrete evidence of productivity gains. Predicts AI innovation “far exceeds” customer adoption pace, creating gap between technical capability and implementation. Forecasts current CEO generation will be last to lead all-human workforces. Admitted AI enabled Salesforce to cut 4,000 jobs while maintaining performance, validating displacement concerns alongside business value demonstration.
https://www.salesforce.com/company/leadership/bios/bio-benioff/
https://www.linkedin.com/in/marcbenioff
16. Bill Gates (Microsoft Co-founder, Philanthropist)
Bill Gates predicts humans won’t be needed “for most things” within a decade as AI provides expert-level guidance across domains, envisioning “free intelligence” democratizing access to medical, educational, and professional advice. He suggests AI could reduce the workweek to two days, though this presumes benefits distribute broadly rather than concentrating among capital owners. Gates emphasizes AI’s transformative potential in education, healthcare, and creativity while acknowledging the labor market disruption requires proactive policy responses including potential universal basic income and massive retraining investments.
https://www.cnbc.com/2025/03/26/bill-gates-on-ai-humans-wont-be-needed-for-most-things.html
American business magnate born October 28, 1955. Co-founded Microsoft in 1975 (stepped down as CEO in 2000). Co-chair of Bill & Melinda Gates Foundation since 2000. Predicts humans won’t be needed “for most things” within decade as AI provides expert-level guidance across domains. Envisions “free intelligence” democratizing medical, educational, and professional advice. Suggests AI could reduce workweek to two days, though benefits distribution remains uncertain. Emphasizes AI’s transformative potential in education, healthcare, and creativity while acknowledging labor disruption requires policy responses including potential UBI.
https://www.gatesnotes.com
https://www.gatesfoundation.org/about/leadership/bill-gates
17. Kai-Fu Lee (Sinovation Ventures Chairman)
Kai-Fu Lee validates his previous prediction that AI will displace 50% of jobs by 2027 as “uncannily accurate,” emphasizing white-collar knowledge work faces faster displacement than blue-collar physical labor. He identifies 2026 as the “year of AI agents” when autonomous systems transition from demonstrations to production deployment at scale. Lee’s perspective incorporates both U.S. and Chinese AI development trajectories, noting China’s aggressive investment in manufacturing automation and service robots creates competitive pressure accelerating global adoption regardless of Western regulatory caution.
Taiwanese computer scientist and businessman born December 3, 1961. Chairman and CEO of Sinovation Ventures. Former President of Google China. Former Microsoft VP and founder of Microsoft Research Asia. Validates prediction that AI displaces 50% of jobs by 2027 as “uncannily accurate.” Identifies 2026 as “year of AI agents” when autonomous systems transition to production deployment. Perspective incorporates both U.S. and Chinese AI trajectories. Author of “AI Superpowers: China, Silicon Valley, and the New World Order” (2018) and “AI 2041” (2021).
https://www.linkedin.com/in/kaifulee
https://www.sinovationventures.com/team.php
18. Emad Mostaque (Former Stability AI Founder)
Emad Mostaque delivers one of the most urgent timelines, predicting within “900 days” AI will perform any screen-based job better than humans, ending human cognitive competitive advantage. He forecasts people won’t distinguish AI from humans in Zoom interactions by 2026, suggesting Turing Test thresholds are effectively crossed for practical purposes. Mostaque’s framing emphasizes the compressed timeline for societal adaptation, arguing current education and workforce development systems are wholly unprepared for the speed of transformation, requiring emergency-level policy interventions that aren’t materializing.
British-Bangladeshi businessman born 1983. Founded Stability AI in 2020, creator of Stable Diffusion. Resigned as CEO in March 2024. Delivers urgent timeline predicting within “900 days” AI performs any screen-based job better than humans, ending human cognitive competitive advantage. Forecasts people won’t distinguish AI from humans in Zoom interactions by 2026. Emphasizes compressed adaptation timeline where education and workforce systems are unprepared for transformation speed, requiring emergency policy interventions that aren’t materializing.
https://twitter.com/emostaque
https://www.linkedin.com/in/emadmostaque
19. Timothy B. Lee (Understanding AI)
Timothy B. Lee provides detailed analytical predictions balancing optimism and skepticism, forecasting U.S. real GDP growth will not exceed 3.5% in 2026—within historical range—arguing AI’s economic boost will be “a fraction of one percent, not enough to push overall economic growth outside its normal range.” He notes OpenAI and Anthropic are “racing to keep up with orders their customers are placing right now,” suggesting real demand rather than speculative bubble. Lee’s 17 predictions cover technical capabilities, market dynamics, and societal impacts with specific, falsifiable forecasts enabling retrospective accuracy assessment.
American journalist and analyst. Creator of Understanding AI newsletter providing detailed analytical predictions balancing optimism and skepticism. Forecasts U.S. real GDP growth won’t exceed 3.5% in 2026—within historical range—arguing AI’s economic boost will be “fraction of one percent.” Notes OpenAI and Anthropic “racing to keep up with orders,” suggesting real demand rather than bubble. His 17 specific, falsifiable predictions enable retrospective accuracy assessment covering technical capabilities, market dynamics, and societal impacts.
20. Rob Toews (Forbes AI Analyst)
Rob Toews synthesizes expert consensus while adding analytical frameworks for evaluating AI’s 2026 trajectory across technical, economic, and strategic dimensions. His predictions emphasize the shift from model-centric to system-centric AI, where individual model capabilities matter less than orchestration, integration, and workflow design. Toews forecasts increased M&A activity as hyperscalers acquire specialized AI companies, consolidation among foundation model providers, and growing divergence between companies that successfully operationalize AI versus those stuck in pilot purgatory, creating winner-take-most dynamics across industries.
https://www.forbes.com/sites/robtoews/2025/12/22/10-ai-predictions-for-2026/
American venture capitalist and AI analyst. General Partner at Radical Ventures focusing on AI investments. Regular Forbes contributor covering AI industry. Synthesizes expert consensus while adding analytical frameworks for evaluating AI’s 2026 trajectory. Predicts shift from model-centric to system-centric AI where orchestration matters more than individual model capabilities. Forecasts increased M&A with hyperscaler acquisitions, consolidation among foundation model providers, and growing divergence between companies successfully operationalizing AI versus pilot purgatory, creating winner-take-most dynamics.
https://www.forbes.com/sites/robtoews/
https://www.radical.vc/team/rob-toews
Honorable Mentions
Yoshua Bengio (Mila Founder, Turing Award Winner)
Canadian computer scientist born March 5, 1964. Full Professor at University of Montreal and founder/scientific director of Mila (Quebec AI Institute). Co-recipient of 2018 Turing Award with Hinton and LeCun. Pioneer of deep learning, particularly work on neural networks and their applications. One of “Godfathers of Deep Learning.” Advocates strongly for AI safety and has become increasingly vocal about existential risks from advanced AI systems.
https://mila.quebec/en/yoshua-bengio
Shane Legg (Google DeepMind Chief AGI Scientist)
New Zealand-British computer scientist. Co-founded DeepMind with Demis Hassabis and Mustafa Suleyman in 2010. Chief AGI Scientist at Google DeepMind. PhD from University of Lugano on machine super intelligence. Early advocate for AGI development with specific focus on measuring progress toward general intelligence. Has predicted 50% chance of human-level AI by 2028.
https://www.deepmind.google/about/people/shane-legg/
https://www.linkedin.com/in/shanelegg
Andrej Karpathy (Founding Member OpenAI, Former Tesla AI Director)
Slovak-Canadian computer scientist born October 23, 1986. Founding member of OpenAI. Former Senior Director of AI at Tesla leading Autopilot Vision team (2017-2022). Currently focused on education through YouTube channel and AI courses. PhD from Stanford under Fei-Fei Li. Known for accessible explanations of complex AI concepts. Created “makemore” educational series on building neural networks from scratch.
https://www.youtube.com/@AndrejKarpathy
Eric Schmidt (Former Google CEO, AI Policy Advocate)
American businessman and software engineer born April 27, 1955. Google CEO 2001-2011, Executive Chairman 2011-2015, Alphabet Executive Chairman 2015-2017. Currently chairs Special Competitive Studies Project on AI policy and U.S.-China tech competition. Warns about AI dangers while advocating for U.S. AI leadership. Delivers high-profile TED talks on AI’s revolutionary potential.
https://www.schmidtfutures.com
https://www.linkedin.com/in/ericschmidt
Tristan Harris (Center for Humane Technology Co-founder)
American technology ethicist born 1984. Co-founder of Center for Humane Technology. Former Google design ethicist. Featured prominently in documentary “The Social Dilemma” (2020). Advocates for responsible AI development, regulation, and addressing AI’s impact on children, mental health, and democracy. Testified before U.S. Congress on technology ethics. Conducts important conversations about AI existential risks and societal implications.
