Bloomberg Technology
What if Big Tech’s Massive Bet on AI Is a False Start?
Big tech is spending hundreds of billions on AI. Is it money well spent? Merryn Somerset Webb explains why it could be a colossal false start. ——– Like this video? Subscribe to Bloomberg Technology on YouTube: Watch the latest full episodes of “Bloomberg Technology” with Caroline Hyde and Ed Ludlow here: Get the…
Bloomberg Technology
Don’t Give Up on AI Chips Yet, Says JoAnne Feeney
The recent selloff in AI stocks has sparked fresh debate over whether more efficient models will reduce demand for chips and data centers. Advisers Capital Management’s JoAnne Feeney explains why she still sees long-term opportunities in AI infrastructure and why she’s more cautious on memory stocks like Micron. She joins Ed Ludlow on “Bloomberg Tech.”…
Bloomberg Technology
Moonshot’s Kimi K3 Reshapes the AI Conversation, Says Bessemer Partner
Moonshot’s Kimi K3 has reignited the debate over the future of AI and whether China’s open-weight models are closing the gap with OpenAI and Anthropic. Bessemer Venture Partners’ Sameer Dholakia joins Bloomberg to discuss why competition is good for AI, where the frontier model makers still have an edge, and why he believes we’re only…
Bloomberg Technology
Nvidia Rolls Out New Chips, WBD Deal In Limbo | Bloomberg Tech 7/21/2026
Bloomberg’s Ed Ludlow breaks down Nvidia’s latest AI chip rollout, as the company says its next-generation processors are now shipping to customers and entering full production. Plus, a judge hits pause on Paramount’s merger with Warner Bros. Discovery, throwing the blockbuster media deal into limbo. And, Sameer Dholakia of Bessemer Venture Partners joins to discuss…
No more panicking when someone says, “Tell me about yourself”
Don’t Give Up on AI Chips Yet, Says JoAnne Feeney
Moonshot’s Kimi K3 Reshapes the AI Conversation, Says Bessemer Partner
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@truevegas
May 21, 2026 at 4:00 pm
Yes 😂 LLMs can learn on the job though. At least Claude can. You just need to save relevant information in its Artifacts and Projects
@orvn
May 21, 2026 at 4:47 pm
Not training on the job, just adding to context, or in best case, accessing a vector storage db in a serial process. The model doesn’t inherently change until training or fine-tuning. There are no inference-training hybrid models at this time. Just elaborate loops.
@orvn
May 21, 2026 at 4:50 pm
I go with Yan Lecun’s thinking here: language is too limited of a training set source. We need to simulate human sensory input (in a non-synthetic way)