A new “unicorn at birth” has entered the AI race. Unconventional AI, a two-month-old startup founded by former Databricks AI chief Naveen Rao, has raised $475M at a $4.5B valuation in a seed round. Backed by a16z, Lightspeed, Lux, DCVC, and Jeff Bezos, the company is targeting one of AI’s hardest problems: building a more energy-efficient computer for next-generation AI workloads as power and compute constraints intensify.

Thinking Machines Labs is reportedly seeking a $50B valuation, just months after raising at a $12B mark. But with co-founder departures and a first product—Tinker—that feels incremental rather than transformative, the jump raises questions. As we’ve covered before, the company still looks more like a research lab than a revenue engine. The widening gap between ambition and output makes this valuation hard to justify.

Meta is cutting around 600 roles from its Superintelligence Labs, impacting FAIR and other AI units in what appears to be a major strategic reset. The move follows a $27B financing deal with Blue Owl Capital and comes just days after Meta hired Andrew Tulloch, co-founder of Thinking Machines Labs. The layoffs suggest Meta is consolidating its AI ambitions — possibly shutting down entire R&D teams to refocus on next-generation foundation models.

Andrew Tulloch, co-founder of Thinking Machines Labs, has left to join Meta, marking another twist in the ongoing AI talent wars. Just months ago, reports suggested Tulloch turned down a $1.5B compensation package from Meta — one of the largest in tech history. His departure follows Thinking Machines’ record-breaking seed round and the launch of its first product, a model-tuning toolkit that some market observers viewed as underwhelming.

A new article from Thinking Machines Labs may hint at where the record-setting startup is heading. The piece explores why LLMs remain nondeterministic even with temperature set to zero tracing the issue to floating-point math across multiple cores. With reports that 95% of AI pilots fail, Thinking Machines seems to be signaling that unpredictability is more than a quirk it’s a core obstacle to scaling AI reliably.

The AI sector has entered an era of unprecedented valuations — with Thinking Machines raising the largest seed round in history and nearly half of all venture capital now flowing into AI. As M.G. Siegler noted on spyglass, OpenAI leads with a $500B secondary valuation, while Anthropic, xAI, and others are pushing past the $100B mark. But as the race tilts from technology to market share and data access, smaller players remain crucial, driving innovation and attracting the att

Meta’s pursuit of AI dominance hit a dramatic note last week with reports that CEO Mark Zuckerberg offered a staggering $1.5 billion compensation package to Thinking Machines Labs co-founder Andrew Tulloch—shortly after the company reportedly declined an acquisition offer. While Meta has denied the claims, the incident underscores the current reality: top-tier AI talent is now the most valuable asset in tech. In a twist of “Airony,” the industry viewed as a threat to human jo

Thinking Machines Labs just revealed they’re building a “multimodal AI” system designed to work with language, visuals, and sound — aiming for what they call “collaborative general intelligence.” Backed by a staggering $2 billion seed round led by a16z and filled with ex-OpenAI talent, the young startup is quickly becoming one of the most closely watched players in the next wave of frontier AI.

Global VC funding hit $91 billion in Q2, with nearly half flowing into AI—a clear sign that the AI boom is driving unprecedented investment momentum - based on Fortune and Crunchbase

What happens when AI systems generate plausible-sounding but completely false information? Welcome to AI hallucinations—fabricated content that's not grounded in context or world knowledge. As AI becomes more sophisticated, distinguishing accurate responses from confident fiction becomes crucial for anyone using these tools.

AI firms are in a fierce talent bidding war, offering huge salaries to top engineers and researchers. From Meta’s aggressive buyouts to startups paying $500K+, it’s a gold rush for skilled tech pros. If you’re technical, this may be your best chance to profit by building the future, not just using it.

Thinking Machines is likely building it's own ChatGPT style model given the background of most of its team (shown here). That could position them as an attractive acquisition target from the mega tech corps who are struggling to keep up with Google, Microsoft and OpenAI.