Older stories and guides from the Convly archive.
OpenAI’s deprecations page sets 24 September 2026 as the shutdown date for the Videos API, sora-2 and sora-2-pro. It is the only 2026 entry on that page with no successor named. Here is what the alternatives cost per second.
A Hugging Face paper page is at huggingface.co/papers/<arXiv-ID>. Swap arxiv.org/abs/ for huggingface.co/papers/ in any arXiv URL to jump straight to
Anthropic has published a hardware standard intended to let AI agents operate physical machines, with early reporting pointing at scientific laboratories as the first serious use case. Here is what the announcement changes for agent developers.
TL;DR:Local LLM models run on your hardware without API calls. Popular options include Llama 3.1 (8B-405B), Mistral 7B, Phi-3, and
Salesforce and Anthropic have announced Claudeforce, a new AI plugin that integrates Claude’s language capabilities directly into Salesforce’s CRM platform for sales automation.
BlackRock’s Li says Nvidia has earnings pricing power going into its second-quarter report, which Yahoo Finance frames as a test of the resurgent AI trade. Here is what the framing means for anyone buying GPUs or paying for model access.
There is no dedicated Ollama integration. You connect OpenClaw to Ollama through Ollama’s OpenAI-compatible API at http://localhost:11434/v1, treating it as
Bloomberg reports that an AI security startup working with Anthropic and Google has raised $140 million. The report is brief, so we separate what is confirmed from the wider industry context.
Nvidia’s move to provide financing to AI customers has positioned it as a banker to the sector, but the arrangement introduces new credit risks to its balance sheet.
Anthropic is reportedly targeting a $2 trillion valuation for a potential public offering, though concerns have surfaced about its most advanced AI model.
TL;DR:Safetensors is a file format for storing machine learning model weights that prevents arbitrary code execution vulnerabilities present in pickle-based
“vLLM omni” almost always refers to running omni-modal models (text + vision + audio + video) on the vLLM inference
