In this episode of the Brainstorm, Sam, Nick, and Research Analyst, Jozef Soja, dive into the latest advancements in AI with a focus on Grok4 and Meta's strategic moves. They explore Grok4's impressive benchmark performances, the real-world implications of AI tool use, and Meta's aggressive investments in AI talent and infrastructure.

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• Grok4 has set new standards in AI benchmarks, particularly in GPQA and Humanities Last Exam, showcasing its advanced reasoning and tool use capabilities.
• Real-world applications still present challenges for Grok4, highlighting the gap between theoretical performance and practical use.
• Meta is making aggressive moves in the AI space, acquiring stakes in companies like Scale AI and investing heavily in AI talent to build a super intelligence team.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

In this episode of FYI, Chief Futurist, Brett Winton, and Analyst Nemo Marjanovic speak with Alex Zhavoronkov, founder and CEO of Insilico Medicine. Together, they explore the promise of artificial intelligence in transforming the drug discovery process—cutting years off timelines and dramatically reducing costs. Alex shares Insilico’s journey from algorithm-first beginnings to a full-stack AI-driven biotech company, highlighting their unique “pan flute” model approach to drug development and the vision of building a “pharmaceutical superintelligence.” The discussion touches on Insilico’s clinical progress, including a molecule that recently completed a Phase 2 trial, and how its generative platforms are helping to tackle complex diseases with a focus on longevity.

• 00:00:00 AI's promise in streamlining the drug discovery process
• 00:03:06 The economics of preclinical development and AI’s role in optimization
• 00:04:43 Potential cost and timeline reductions: $2.4B down to $600M, 13 years to 8
• 00:07:39 Comparing Insilico’s approach to peers like Recursion and AbSci
• 00:10:35 Literature-driven vs. biology-driven models in drug discovery
• 00:13:07 Why a dominant AI platform could reshape biotech industry consolidation
• 00:14:57 Why biologics may be more suited to AI than small molecules
• 00:17:35 Alex Zhavoronkov on founding Insilico and his mission in longevity science
• 00:21:00 From algorithms to real drugs: Insilico’s transition to clinical development
• 00:23:15 Managing the pace of AI progress vs. the slow cycle of experimental validation
• 00:27:10 How “pharmaceutical superintelligence” enables prompt-to-drug workflows
• 00:32:26 Validation, trust, and why Insilico runs on both old and frontier models
• 00:39:22 The “pan flute” architecture: stacking specialized models with reinforcement learning
• 00:42:36 Building and training a unified multimodal model for chemistry and biology
• 00:45:32 Public data, clean pipelines, and Insilico’s automated validation lab
• 00:50:47 The business model behind Insilico: selling candidates and licensing platforms
• 00:55:12 Why pharma buyers care more about data room quality than pricing
• 01:00:25 On profitability, licensing success, and the dream of a self-sustaining AI biotech
• 01:01:38 Longevity and the search for fundamental mechanisms of aging

In this episode of the Brainstorm, Sam and Nick dive into Robinhood's latest event, exploring its ambitious moves in the crypto market. They discuss how Robinhood is leveraging product velocity to outpace competitors, tokenize US stocks, and introduce innovative features like crypto staking and perpetual futures. They analyze the implications of these developments for the financial services landscape and what it means for the future of investing. 

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• Robinhood's focus on product velocity to outpace competitors. 
• Tokenization of US stocks and private company shares in the EU. 
• Development of Robinhood's own layer two blockchain. 
• Introduction of crypto staking in the US with higher yields. 
• Exploration of new revenue lines, including a crypto-backed gold card. 
• Building a comprehensive financial ecosystem for the next generation.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

Brett Winton and ARK analyst Jozef Soja dive deep into the rapidly evolving world of AI agents—software entities that are increasingly automating enterprise functions like customer support. They explore why AI agents are gaining traction, how they’re priced, and the potential for a new kind of agent-versus-agent arms race between companies and consumers. Later in the episode, they’re joined by Dr. Alan Bekker, founder of eSelf.ai and former Head of Conversational AI at Snap, who shares his journey from building voice agents for call centers to launching a real-time, face-to-face AI tutoring platform. Alan offers insights into how the rise of large language models (LLM) is reshaping education, what makes a great AI tutor, and why a visual, embodied presence is crucial for learning.

• 00:00:00 What enterprise AI agents actually do and how companies like Salesforce are pricing them
• 00:03:41 Why $2 per AI conversation may already undercut human support costs
• 00:05:04 The Return On Investment (ROI) model behind agent adoption and enterprise productivity
• 00:06:41 Why agent-based software may retain higher pricing power than other AI tools
• 00:09:11 The coming arms race: AI agents negotiating with other AI agents
• 00:12:30 Scaling demand for customer service with intelligent automation
• 00:15:04 Vertical vs. horizontal Software as a Service (SaaS) in the AI agent ecosystem
• 00:16:43 AI’s impact across the software stack—SaaS, Platform as a Service (PaaS) , and Infrastructure as a Service (IaaS)
• 00:17:56 Why building your own AI apps may soon be cheaper than onboarding SaaS
• 00:20:01 ARK's  internal hackathon and how non-engineers are becoming developers
• 00:20:29 Guest: Dr. Alan Bekker joins to discuss the evolution of conversational AI
• 00:22:04 The journey from decision trees to LLMs: Lessons from Snap’s AI team
• 00:27:32 Seeing GPT’s impact from inside: OpenAI’s early partner outreach
• 00:31:47 Why face-to-face AI tutors found strong product-market fit in education
• 00:33:59 eSelf’s go-to-market strategy: Partnering with publishers as a business to business to consumer (B2B2C) wedge
• 00:36:24 Pricing real-time AI tutoring tools in a margin-conscious market
• 00:40:00 Business to consumer (B2C) aspirations: Moving toward a direct-to-student tutoring product
• 00:44:56 What’s still missing for real-time AI to match human-level teaching
• 00:48:03 The psychological impact of avatars: Building trust through embodied agents
• 00:51:43 Why personalization—not just LLM knowledge—matters in tutoring
• 00:54:20 Democratizing learning: LLMs as the end of expert-driven education

In this episode, Sam Korus, Nick Grous, and Daniel Maguire discuss the future of robotaxis, focusing on Tesla's advancements in autonomous vehicle technology compared to Waymo. They explore the implications of Tesla's data advantage, production capabilities, and the regulatory landscape affecting the rollout of robotaxis. The conversation also delves into market dynamics, consumer behavior, and potential partnerships in the ride-hailing space, highlighting the challenges and opportunities ahead for Tesla and the autonomous vehicle industry.

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• Tesla is set to launch its robotaxi service in Austin, Texas.
• Tesla has a significant data advantage over Waymo, gathering nearly 10 million miles of data daily.
• The cost of Tesla vehicles is significantly lower than Waymo's, making them more accessible.
• Safety is a top priority for Tesla, influencing their cautious rollout strategy.
• Tesla's production capabilities allow them to scale much faster than Waymo.
• The regulatory environment is evolving, potentially easing the path for autonomous vehicles.
• Tesla's ridership model could allow for greater market penetration compared to Waymo.
• Consumer behavior will play a crucial role in the adoption of robotaxis.
• The partnership strategy of Tesla differs from Waymo's, focusing on direct consumer engagement.
• The conversation highlights the skepticism surrounding the rapid deployment of autonomous vehicles.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

In this episode, Sam Korus discusses stablecoins with Lorenzo Valente and Raye Hadi. They explore the definition of stablecoins, their impact on the US dollar, and the competitive dynamics between major players like Tether and Circle. The conversation delves into the role of stablecoins in emerging markets, their business models, and the potential convergence with AI transactions. They also address concerns regarding stability, privacy, and the future of stablecoins in the financial ecosystem.

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• Stablecoins are pegged to a dollar value to reduce volatility.
• Tether and Circle dominate the stable coin market with 85% share.
• Emerging markets are increasingly using stablecoins for transactions.
• The business model of stablecoins relies on reserve backing and transaction fees.
• Stablecoins can unlock significant amounts of dead capital in emerging markets.
• AI agents may prefer stablecoins for their programmable nature.
• Concerns about de-pegging and liquidity are prevalent in the market.
• The future of stablecoins could be expansive if regulatory frameworks support them.
• Stablecoins are currently about 1% of the US money supply.
• The potential for stablecoin supply to grow to 1.5 trillion in the next five years.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

In this episode of FYI – For Your Innovation, ARK's Director of Research Brett Winton sits down with Brad Feld — co-founder of Foundry, Techstars, and longtime venture capitalist — to unpack his latest thinking on startup communities, mentorship, and how founders can build better networks by giving first. After taking time away from public life to reflect, Brad returns with a new book, Give First: The Power of Mentorship, and a sharpened view on the distinction between transactional ecosystems and community-led innovation. He shares lessons from nearly two decades with Techstars, thoughts on remote vs. in-person work post-COVID, and how mentorship can be redesigned for the next generation of entrepreneurs. The conversation also explores the cultural shifts introduced by AI, the hidden friction in monetizing online engagement, and why Brad believes the best way to shape a network is to invest in others before you know what you’ll get in return.

• 00:00:00 Why Brad Feld “hibernated” from public life and how it changed his perspective
• 00:04:24 From default yes to default no: Reclaiming time and creative energy
• 00:06:28 Navigating remote work: Company culture and post-COVID office dynamics
• 00:09:49 When revenue goes negative: COVID-era crisis stories from Rover and SeatGeek
• 00:12:25 The Give First philosophy — and how it became Techstars’ guiding principle
• 00:17:50 Finding mentorship as a founder: What works and what definitely doesn’t
• 00:19:15 The power of peer mentorship and showing up without expectations
• 00:23:16 How online culture’s transactional mindset erodes community trust
• 00:26:00 Boulder Startup Week and the importance of local founder energy
• 00:30:41 Brad’s Random Day tradition: 15-minute meetings, one goal per person
• 00:35:17 Techstars vs. YC: Origins of the mentor-driven accelerator model
• 00:40:27 Building startup communities from scratch: What actually works
• 00:46:05 Founders must lead: Differentiating between startup communities and ecosystems
• 00:49:00 Mentorship at scale: Applying Techstars’ playbook to community growth
• 00:54:08 Frictionless networks: Why “Give First” accelerates stronger connections
• 01:00:16 AI’s impact on software development, legal workflows, and personal productivity
• 01:04:07 Coding with AI: Brad’s firsthand experience building a web app with Cursor

In this episode, Nicholas Grous and Sam Korus are joined by ARK Chief Futurist, Brett Winton, to delve into the Mary Meeker AI Trends Report, discussing the rapid adoption of AI technologies, the evolving role of AI in trust and validation, and the changing landscape of search behavior. They explore the monetization of AI, the investment landscape, and the future of autonomous vehicles, concluding with a positive outlook on AI's trajectory.

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• The rapid pace of AI adoption is unprecedented.
• AI is reshaping how we validate information and trust sources.
• Search behavior is evolving with the integration of AI.
• Monetization strategies for AI are becoming clearer.
• Investment in AI infrastructure is crucial for growth.
• Autonomous vehicles are on the brink of mainstream adoption.
• AI's role in education could revolutionize assessment methods.
• The competition between the US and China in AI is intensifying.
• Consumer behavior is shifting towards AI-driven solutions.
• Optimism about AI's future is warranted despite pessimistic narratives.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

In this episode, Nicholas Grous and Sam Korus discuss the recent Google I.O. event and OpenAI's significant acquisition, exploring the implications for generative AI and the competitive landscape between Google and Apple. They delve into Google's unified strategy for integrating AI across its ecosystem, the introduction of new tools for creators, and the potential future of AI hardware. The conversation highlights the challenges and opportunities for both tech giants as they navigate the evolving AI landscape.

If you know ARK, then you probably know about our long-term research projections, like estimating where we will be 5-10 years from now! But just because we are long-term investors, doesn’t mean we don’t have strong views and opinions on breaking news. In fact, we discuss and debate this every day. So now we’re sharing some of these internal discussions with you in our new video series, “The Brainstorm”, a co-production from ARK and Public.com. Tune in every week as we react to the latest in innovation. Here and there we’ll be joined by special guests, but ultimately this is our chance to join the conversation and share ARK’s quick takes on what’s going on in tech today.

Key Points From This Episode:

• Google's I.O. showcased a unified strategy for generative AI.
• The integration of AI into Android and Chrome is a key focus.
• Project Mariner aims to enhance browser capabilities with AI.
• Veo 3 represents a significant advancement in AI video generation.
• Generative AI tools are democratizing content creation.
• Apple needs to innovate quickly to stay competitive in AI.
• The future of AI hardware may not require screens.
• Privacy concerns will shape the design of new AI devices.
• Google's consumer-facing products are still strong despite past failures.
• The competition between Google and Apple will define the AI landscape.

For more updates on Public.com:

Website: https://public.com/

YouTube: @publicinvest

X: https://twitter.com/public

In this episode of FYI – For Your Innovation, Brett Winton and ARK analyst Nemo Despot sit down with Generate Biomedicines CEO Mike Nally and CFO Jason Silvers to explore how generative AI is transforming the discovery and development of protein-based therapeutics. Founded in 2018 by Flagship Pioneering, Generate Biomedicines is building a “self-driving lab” that combines machine learning, cryo-electron microscopy (cryo-EM), and high-throughput wet lab automation to dramatically accelerate drug development. The conversation dives into how Generate is reimagining protein therapeutics — going beyond trial-and-error methods to a data-first, design-driven model for creating novel medicines. The team discusses the company’s proprietary approach to integrating structural biology with functional data, the economic implications of reducing time-to-market from 13 years to under 9, and how their platform could unlock treatments for diseases that have been historically undruggable. They also touch on strategic partnerships, scalability, and how AI is shifting the biotech business model from artisanal science to an industrialized, data-driven enterprise.

• 00:01:30 Why Generate Biomedicines is rethinking protein drug discovery from first principles
• 00:04:40 How their structure-first approach differs from peers like AbSci and Recursion
• 00:07:04 Using cryo-EM to build proprietary protein interaction datasets
• 00:10:57 Traditional drug discovery is random, expensive, and inefficient — here’s how Generate is changing that
• 00:16:58 From concept to clinic in 18–24 months: Accelerating timelines through AI
• 00:20:47 Going beyond efficiency: Unlocking access to undruggable biology
• 00:24:48 Turning cryo-EM into a high-throughput data engine for model training
• 00:31:20 The long-term vision: Patient-specific protein therapeutics
• 00:40:00 Why scalability gives Generate an edge over traditional biotech
• 00:47:52 The future of biotech as a research & development (R&D) sharing economy
• 00:54:19 Adapting fast: Keeping pace with generative AI advances across the stack
• 01:00:16 The KPI (key performance indicator) for platform success: Rate of improvement