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Last chance to join! In tomorrow's webinar [4], Martin Casado, General Partner at Andreessen Horowitz, reveals how leading startups and public companies alike are building monetization operating models for the AI era.
A revamped version of Siri that uses a custom Gemini-based model is expected to roll out in March next year. Google is reportedly developing the model, which will run on Apple's Private Cloud Compute servers to power Siri. Apple is reportedly running into problems with the launch of Apple Intelligence in China. It is being mired by regulatory issues, so the launch is now a rolling target.
Sam Altman grew testy when pressed about OpenAI's ability to fund $1.4 trillion in committed spending, snapping at interviewer Brad Gerstner with, "If you want to sell your shares, I'll find you a buyer". Altman said OpenAI is doing "well more" than the previously reported $13 billion in annual revenue and suggested the company could reach $100 billion by 2027, but denied rumors of an IPO in 2026.
Ilya Sutskever plotted for over a year with Mira Murati to remove Sam Altman as OpenAI CEO. Dario Amondei wanted Greg Brockman fired and himself in charge of all research. Murati told Sutskever that Altman had pitted her against Daniela Amondei. Sutskever wrote a 52-page-long memo to get Altman fired and also a separate document on Brockman. OpenAI is paying Sutskever's legal bills.
Language models use em-dashes so much that real humans who like using them have stopped out of fear of being confused with AI. It's surprisingly hard to prompt models to avoid using em-dashes. Researchers still don't really know why language models use them so much. This article looks at some possible explanations.
Meta has proposed the "Agents Rule of Two" to reduce prompt injection risks in AI agents by limiting them to no more than two of three capabilities in a session: handling untrusted inputs, accessing private data, or taking external actions.
Recent advancements in OCR models, such as Chandra and Deepseek, eliminate traditional scripting by using vision transformers that convert raw pixels into semantic tokens. These models improve accuracy by understanding and compressing visual data into concise tokens before decoding them into text, allowing context-aware text recognition. Deepseek-ocr achieves this efficiently with ~10x compression, enabling flexible adaptation to different fonts and handwriting styles without retraining.
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After weeks of user reports claiming Codex had gotten worse, echoing a perennial concern that frontier labs secretly downgrade their models, OpenAI assembled a squad to investigate every possible culprit and publish their findings. The team found no smoking gun, but instead uncovered a catalog of small bugs: older hardware subtly dragging down performance, a constrained sampling bug that made the model switch to Korean mid-sentence, and context compaction that quietly degraded accuracy in long conversations.
Tongyi DeepResearch is a full open-source Web Agent that achieves performance on par with OpenAI's DeepResearch across a comprehensive suite of benchmarks. It is specifically designed for long-horizon, deep information-seeking tasks. This post shares a complete and battle-tested methodology for creating advanced agents like Tongyi DeepResearch.
Small language models are helping companies get real work done and reduce headcount. They are more affordable than large language models and, in some cases, better suited to the tasks at hand. The impact that AI is having on corporate productivity gains is the result of human engineers getting better at stitching together smaller, simpler AIs. Many companies have built internal knowledge factories that daisy chain together small AIs.
AI-generated musicians have debuted on Billboard charts each week for the past month. One artist, Xania Monet, scored a No. 1 hit on the R&B sales chart and a multimillion-dollar record deal.
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Amazon's Q3 earnings revealed that the company gained $9.5 billion from Anthropic ownership.
At the time, Anthropic was valued at $18 billion - the company will soon be valued at around $300 billion.
Google AI Studio now offers logs and datasets features to help developers monitor AI app performance, debug more effectively, and improve output quality.
Treating beneficial AGI as impossible could be a self-fulfilling prophecy that cedes the field to those who don't care about safety at all.
OpenAI has voluntarily transferred more of the public's entitled value to private interests than any charitable organization ever.