Tag: output

  • Simon Willison’s Weblog: GPT-5-Codex

    Source URL: https://simonwillison.net/2025/Sep/23/gpt-5-codex/#atom-everything Source: Simon Willison’s Weblog Title: GPT-5-Codex Feedly Summary: GPT-5-Codex OpenAI half-relased this model earlier this month, adding it to their Codex CLI tool but not their API. Today they’ve fixed that – the new model can now be accessed as gpt-5-codex. It’s priced the same as regular GPT-5: $1.25/million input tokens, $10/million…

  • The Register: Nearly half of businesses suffered deepfaked phone calls against staff

    Source URL: https://www.theregister.com/2025/09/23/gartner_ai_attack/ Source: The Register Title: Nearly half of businesses suffered deepfaked phone calls against staff Feedly Summary: AI attacks on the rise A survey of cybersecurity bosses has shown that 62 percent reported attacks on their staff using AI over the last year, either by the use of prompt injection attacks or faking…

  • Cloud Blog: AI Innovators: How JAX on TPU is helping Escalante advance AI-driven protein design

    Source URL: https://cloud.google.com/blog/topics/customers/escalante-uses-jax-on-tpus-for-ai-driven-protein-design/ Source: Cloud Blog Title: AI Innovators: How JAX on TPU is helping Escalante advance AI-driven protein design Feedly Summary: As a Python library for accelerator-oriented array computation and program transformation, JAX is widely recognized for its power in training large-scale AI models. But its core design as a system for composable function…

  • Slashdot: MediaTek Launches Improved AI Processor To Compete With Qualcomm

    Source URL: https://hardware.slashdot.org/story/25/09/23/0434209/mediatek-launches-improved-ai-processor-to-compete-with-qualcomm Source: Slashdot Title: MediaTek Launches Improved AI Processor To Compete With Qualcomm Feedly Summary: AI Summary and Description: Yes Summary: MediaTek’s launch of the Dimensity 9500 mobile processor enhances AI capabilities on devices, directly competing with Qualcomm in the performance of AI tasks. This advancement, built on a sophisticated 3-nanometer process, has…

  • Simon Willison’s Weblog: Quoting Kate Niederhoffer, Gabriella Rosen Kellerman, Angela Lee, Alex Liebscher, Kristina Rapuano and Jeffrey T. Hancock

    Source URL: https://simonwillison.net/2025/Sep/22/workslop/ Source: Simon Willison’s Weblog Title: Quoting Kate Niederhoffer, Gabriella Rosen Kellerman, Angela Lee, Alex Liebscher, Kristina Rapuano and Jeffrey T. Hancock Feedly Summary: We define workslop as AI generated work content that masquerades as good work, but lacks the substance to meaningfully advance a given task. Here’s how this happens. As AI…

  • Simon Willison’s Weblog: Four new releases from Qwen

    Source URL: https://simonwillison.net/2025/Sep/22/qwen/ Source: Simon Willison’s Weblog Title: Four new releases from Qwen Feedly Summary: It’s been an extremely busy day for team Qwen. Within the last 24 hours (all links to Twitter, which seems to be their preferred platform for these announcements): Qwen3-Next-80B-A3B-Instruct-FP8 and Qwen3-Next-80B-A3B-Thinking-FP8 – official FP8 quantized versions of their Qwen3-Next models.…

  • Slashdot: Hundreds of Google AI Workers Were Fired Amid Fight Over Working Conditions

    Source URL: https://tech.slashdot.org/story/25/09/20/2338214/hundreds-of-google-ai-workers-were-fired-amid-fight-over-working-conditions?utm_source=rss1.0mainlinkanon&utm_medium=feed Source: Slashdot Title: Hundreds of Google AI Workers Were Fired Amid Fight Over Working Conditions Feedly Summary: AI Summary and Description: Yes Summary: The article discusses the difficult working conditions of AI raters contracted by Google through Hitachi’s GlobalLogic, highlighting issues such as high pressure, job disillusionment, and the precarious nature of…

  • Simon Willison’s Weblog: Grok 4 Fast

    Source URL: https://simonwillison.net/2025/Sep/20/grok-4-fast/ Source: Simon Willison’s Weblog Title: Grok 4 Fast Feedly Summary: Grok 4 Fast New hosted reasoning model from xAI that’s designed to be fast and extremely competitive on price. It has a 2 million token context window and “was trained end-to-end with tool-use reinforcement learning". It’s priced at $0.20/million input tokens and…