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
Why the US Military Is Betting on Portable Nuclear
Radiant has won a $750 million US Army contract to provide 15 portable nuclear microreactors under the Janus program. President and COO Tori Shivanandan discusses the technology behind the reactors, the military’s push for resilient energy, and what Radiant needs to do next to scale production. She joins Ed Ludlow on “Bloomberg Tech.” ——– Like…
Bloomberg Technology
Madrona’s IA40 List Highlights the Next Generation of Tech Leaders
The IA40 list from Madrona is back, spotlighting the private companies shaping the next phase of AI. Matt McIlwain, managing director at Madrona, explains how the list is assembled, why OpenAI, Anthropic and Databricks dominate AI fundraising, and how a successful Anthropic IPO could open the door for a new wave of public offerings in…
Bloomberg Technology
Nvidia Deepens Chip Ties With $3.5 Billion MediaTek Bet | Bloomberg Tech 8/31/2026
Bloomberg’s Ed Ludlow breaks down Nvidia’s $3.5 billion investment in MediaTek, deepening its collaboration with the Taiwanese chipmaker and demonstrating how the AI leader plans to tackle Big Tech efforts to build custom silicon. Plus, a look at Tim Cook’s last day as CEO of Apple before John Ternus takes the reins on September 1st.…
Why the US Military Is Betting on Portable Nuclear
Madrona’s IA40 List Highlights the Next Generation of Tech Leaders
Nvidia Deepens Chip Ties With $3.5 Billion MediaTek Bet | Bloomberg Tech 8/31/2026
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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)