🕶️ Trump pardons Binance’s founder

AI labs are spending billions to build massive data centers and scale up large language models, betting that more computing power will unlock superintelligent systems. But many researchers now argue that this “bigger is better” approach is reaching its limits. Sara Hooker, a former Cohere and Google Brain researcher, is taking a different path with her new startup, Adaption Labs, which focuses on building AI systems that can learn and adapt continuously from real-world experience—efficiently and without massive infrastructure.

Hooker believes adaptive learning could make AI smarter, cheaper, and more accessible, challenging the dominance of a few large labs. While companies like OpenAI and Meta continue to pour money into scaling and reinforcement learning, Adaption Labs is betting that real-time learning will redefine how AI evolves. The startup has reportedly raised between $20 million and $40 million and plans to hire globally, aiming to prove that true intelligence comes from experience—not just scale.

Your TAM (Total Addressable Market) is not the size of the problem. It's not a percentage of a trillion-dollar industry. And it's definitely not a number you can pull from a Google search and shrink down to fit your pitch. In this video, we break down exactly how to build a solid TAM slide for your pitch deck—one that investors will actually take seriously. We’ll debunk common mistakes, walk through bottom-up calculations, and show you how to estimate SAM and SOM the right way.

Hiring great engineers shouldn’t feel like finding a needle in an AI-generated haystack. G2i connects you with pre-vetted contract and full-time developers—no scammers, no endless resume piles, just top talent with 5+ years of experience across every major tech stack.

We’ve already helped teams at Meta, Microsoft, and fast-growing startups like Shopmonkey and 1Password hire faster, smarter, and with full transparency through recorded technical interviews.

Whether you need one engineer or a whole team, we’ve got over 8,000 ready to go.

Imagine shopping online and hitting a Help Me Decide button. Instead of endless scrolling, an AI guide steps in—offering a tailored pick and explaining why it fits you. Suddenly, choice paralysis turns into confidence.

The result? People buy faster and spend more. Persuasive reasoning, not ads, becomes the real advantage. Sellers start rewriting titles, refining features, and curating reviews to align with the “why.” Marketplaces tighten their hold as behavior data stacks up, making each suggestion smarter than the last.

But there’s a flip side. Questions about privacy, consent, and how these systems persuade users will grow louder. Affiliate sites and comparison engines may lose traffic as shoppers rely directly on these built-in advisors. And once one platform launches it, others will rush to follow—embedding AI shopping sherpas right into the checkout flow.