Jeff Bezos' New AI Venture Quietly Acquired an Agentic Computing Startup Project Prometheus has raised over $6 billion in funding and hired over 100 employees, a handful of whom joined through its acquisition of General Agents, according to records and sources. In early June, tech entrepreneur Vik Bajaj took over Saison, a two-Michelin star restaurant in San Francisco, for an off-the-record dinner to talk about AI with journalists and a handful of scientists. In attendance was Sherjil Ozair, a late addition who had previously held senior research roles at DeepMind and Tesla . The following day, Bajaj and Ozair were on their way to making a deal, public records show. Bajaj didn't mention it at the dinner, but earlier this year he had begun working with Amazon executive chairman Jeff Bezos on a new AI venture called Project Prometheus.

Financial applications of large language models (LLMs) require factual reliability and computational efficiency, yet current systems often hallucinate details and depend on prohibitively large models. We propose FISCAL (Financial Synthetic Claim-Document Augmented Learning), a modular framework for generating synthetic data tailored to financial fact-checking. Using FISCAL, we generate a dataset called FISCAL-data and use it to train MiniCheck-FISCAL, a lightweight verifier for numerical financial claims. MiniCheck-FISCAL outperforms its baseline, surpasses GPT-3.5 Turbo and other open-source peers of similar size, and approaches the accuracy of much larger systems (20x), such as Mixtral-8x22B and Command R+. On external datasets FinDVer and Fin-Fact, it rivals GPT-4o and Claude-3.5 while outperforming Gemini-1.5 Flash. These results show that domain-specific synthetic data, combined with efficient fine-tuning, enables compact models to achieve state-of-the-art accuracy, robustness, and scalability for practical financial AI. The dataset and scripts are available in the project repository (link provided in the paper).

'We excel at every phase of AI': Nvidia CEO quells Wall Street fears of AI bubble amid market selloff Global share markets rose after Nvidia posted third-quarter earnings that beat Wall Street estimates, assuaging for now concerns about whether the high-flying valuations of AI firms had peaked. On Wednesday, all eyes were on Nvidia, the bellwether for the AI industry and the most valuable publicly traded company in the world, with analysts and investors hoping the chipmaker's third-quarter earnings would dampen fears that a bubble was forming in the sector. Jensen Huang, founder and CEO of Nvidia, opened the earnings call with an attempt to dispel those concerns, saying that there was a major transformation happening in AI, and Nvidia was foundational to that transformation. "There's been a lot of talk about an AI bubble," said Huang. "From our vantage point, we see something very different. As a reminder, Nvidia is unlike any other accelerator. We excel at every phase of AI from pre-training to post-training to inference."

Record sales, a strong financial forecast, and CEO Jensen Huang's impassioned arguments on his company's earnings call weren't enough to push Nvidia shares back to their October high. Nvidia CEO Jensen Huang speaks to the media in Tainan, Taiwan on November 7, 2025. Nvidia CEO Jensen Huang didn't need any prompting on Wednesday to address the elephant in the room . "There's been a lot of talk about an AI bubble," he said on an earnings call before quickly getting to his main point: "From our vantage point, we see something very different." Huang went on to spend about five minutes trying to explain how the chipmaker, which has soared to become the world's most valuable publicly traded company over the past three years, would be able to sustain unprecedented customer demand.

Amid a blackout of data due to the government shutdown, the $5tn chipmaker's report took on wider significance Markets expectations around Wednesday's quarterly earnings report by the most valuable publicly traded company in the world had risen to a fever pitch. Anxiety over billions in investment in artificial intelligence pervaded, in part because the US has been starved of reliable economic data by the recent government shutdown. Investors hoped that both questions would be in part answered by Nvidia's earnings and by a jobs report due on Thursday morning. "This is a'So goes Nvidia, so goes the market' kind of report," Scott Martin, chief investment officer at Kingsview Wealth Management, told Bloomberg in a concise summary of market sentiment. The prospect of a market mood swing had built in advance of the earnings call, with options markets anticipating Nvidia's shares could move 6%, or $280bn in value, up or down.

Nvidia has forecast fourth-quarter revenue above Wall Street estimates and is betting on booming demand for its AI chips from cloud providers even as widespread concerns of an artificial intelligence bubble grow stronger. The world's most valuable company expects fourth-quarter sales of $65bn, plus or minus 2 percent, compared with analysts' average estimate of $61.66bn, according to data compiled by LSEG. Anthropic's AI hacking claims divide experts "The AI ecosystem is scaling fast with more new foundation model makers, more AI start-ups across more industries and in more countries. AI is going everywhere, doing everything, all at once," Nvidia CEO Jensen Huang said in a statement. Before the results, doubts had pushed Nvidia shares down nearly 8 percent in November after a 1,200 percent surge in the past three years.

Chip giant Nvidia beat Wall Street's expectations for revenue and upcoming sales, easing investor concerns about heavy artificial intelligence (AI) spending that have unsettled markets. In its quarterly earnings report on Wednesday, the firm said revenue for the three months to October jumped 62% to $57bn, driven by demand for its chips used in AI data centres. Sales from that division rose 66% to more than $51bn. Fourth-quarter sales forecasts in the range of $65bn also topped estimates, sending shares in Nvidia more than 3% higher in after-hours trading. Nvidia, the world's most valuable company, is seen as a bellwether for the AI boom.

Financial documents like earning reports or balance sheets often involve long tables and multi-page reports. Large language models have become a new tool to help numerical reasoning and understanding these documents. However, prompt quality can have a major effect on how well LLMs perform these financial reasoning tasks. Most current methods tune prompts on fixed datasets of financial text or tabular data, which limits their ability to adapt to new question types or document structures, or they involve costly and manually labeled/curated dataset to help build the prompts. We introduce a self-improving prompt framework driven by data-augmented optimization. In this closed-loop process, we generate synthetic financial tables and document excerpts, verify their correctness and robustness, and then update the prompt based on the results. Specifically, our framework combines a synthetic data generator with verifiers and a prompt optimizer, where the generator produces new examples that exposes weaknesses in the current prompt, the verifiers check the validity and robustness of the produced examples, and the optimizer incrementally refines the prompt in response. By iterating these steps in a feedback cycle, our method steadily improves prompt accuracy on financial reasoning tasks without needing external labels. Evaluation on DocMath-Eval benchmark demonstrates that our system achieves higher performance in both accuracy and robustness than standard prompt methods, underscoring the value of incorporating synthetic data generation into prompt learning for financial applications.

Next-gen networking tech, sometimes powered by light instead of electricity, is emerging as a critical piece of AI infrastructure. The new era of Silicon Valley runs on networking--and not the kind you find on LinkedIn. As the tech industry funnels billions into AI data centers, chip makers both big and small are ramping up innovation around the technology that connects chips to other chips, and server racks to other server racks. Networking technology has been around since the dawn of the computer, critically connecting mainframes so they can share data. In the world of semiconductors, networking plays a part at almost every level of the stack--from the interconnect between transistors on the chip itself, to the external connections made between boxes or racks of chips.

SoftBank sells Nvidia stake for $5.8 billion to fund AI bets SoftBank Group founder Masayoshi Son is aggressively seeking to capitalize on booming investment in AI and chips, even as he scales back other investments. SoftBank Group sold its entire stake in Nvidia for $5.83 billion to help bankroll artificial intelligence investments, even as investors question the amount of capital pouring into a technology with uncertain returns. Founder Masayoshi Son has been unwinding positions to pay for a plethora of AI projects, from Stargate data centers with OpenAI and Oracle to robot manufacturing sites in the United States. The Nvidia exit coincides with a growing debate about whether spending by big tech firms like Meta Platforms and Alphabet -- expected to surpass $1 trillion in coming years -- will produce commensurate returns. SoftBank's stock slid more than 10% in Tokyo on Wednesday, highlighting how investors remain nervous about lofty tech valuations.