Page de couverture de 📆 ThursdAI - Aug 14 - A week with GPT5, OSS world models, VLMs in OSS, Tiny Gemma & more AI news

📆 ThursdAI - Aug 14 - A week with GPT5, OSS world models, VLMs in OSS, Tiny Gemma & more AI news

📆 ThursdAI - Aug 14 - A week with GPT5, OSS world models, VLMs in OSS, Tiny Gemma & more AI news

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 Hey everyone, Alex here 👋Last week, I tried to test GPT-5 and got really surprisingly bad results, but it turns out, as you'll see below, it's partly because they had a bug in the router, and partly because ... well, the router itself! See below for an introduction, written by GPT-5, it's actually not bad?Last week was a whirlwind. We live‑streamed GPT‑5’s “birthday,” ran long, and then promptly spent the next seven days poking every corner of the new router‑driven universe.This week looked quieter on the surface, but it actually delivered a ton: two open‑source world models you can drive in real time, a lean vision‑language model built for edge devices, a 4B local search assistant that tops Perplexity Pro on SimpleQA, a base model “extraction” from GPT‑OSS that reverses alignment, fresh memory features landing across the big labs, and a practical prompting guide to unlock GPT‑5’s reasoning reliably.We also had Alan Dao join to talk about Jan‑v1 and what it takes to train a small model that consistently finds the right answers on the open web—locally.Not bad eh? Much better than last time 👏 Ok let's dive in, a lot to talk about in this "chill" AI week (show notes at the end as always) first open source, and then GPT-5 reactions and then... world models!00:00 Introduction and Welcome00:33 Host Introductions and Health Updates01:26 Recap of Last Week's AI News01:46 Discussion on GPT-5 and Prompt Techniques03:03 World Models and Genie 303:28 Interview with Alan Dow from Jan04:59 Open Source AI Releases06:55 Big Companies and APIs10:14 New Features and Tools14:09 Liquid Vision Language Model26:18 Focusing on the Task at Hand26:18 Reinforcement Learning and Reward Functions26:35 Offline AI and Privacy27:13 Web Retrieval and API Integration30:34 Breaking News: New AI Models30:41 Google's New Model: Gemma 333:53 Meta's Dino E3: Advancements in Computer Vision38:50 Open Source Model Updates45:56 Weights & Biases: New Features and Updates51:32 GPT-5: A Week in Review55:12 Community Outcry Over AI Model Changes56:06 OpenAI's Response to User Feedback56:38 Emotional Attachment to AI Models57:52 GPT-5's Performance in Coding and Writing59:55 Challenges with GPT-5's Custom Instructions01:01:45 New Prompting Techniques for GPT-501:04:10 Evaluating GPT-5's Reasoning Capabilities01:20:01 Open Source World Models and Video Generation01:27:54 Conclusion and Future ExpectationsOpen Source AIWe've had quite a lot of Open Source this week on the show, including a breaking news from the Gemma team!Liquid AI's drops LFM2-VL (X, blog, HF)Let's kick things off with our friends at Liquid AI who released LFM2-VL - their new vision-language models coming in at a tiny 440M and 1.6B parameters.Liquid folks continue to surprise with speedy, mobile device ready models, that run 2X faster vs top VLM peers. With a native 512x512 resolution (which breaks any image size into 512 smart tiles) and an OCRBench of 74, this tiny model beats SmolVLM2 while being half the size. We've chatted with Maxime from liquid about LFM2 back in july, and it's great to see they are making them multimodal as well with the same efficiency gains!Zhipu (z.ai) unleashes GLM-4.5V - 106B VLM (X, Hugging Face)In another "previous good model that now has eyes" release, the fine folks from Zhipu continued training thier recently released (and excelled) GLM 4.5-air with a vision encoder, resulting in probably one of the top vision models in the open source!It's an MoE with only 12B active parameters (106B total) and gets SOTA across 42 public vision-language benches + has a "thinking mode" that reasons about what it sees.Given that GLM-4.5Air is really a strong model, this is de fact the best visual intelligence in the open source, able to rebuild websites from a picture for example and identify statues and locations!Jan V1 - a tiny (4B) local search assistant QwenFinetune (X, Hugging Face)This one release got a lot of attention, as the folks at Menlo Research (Alan Dao who came to chat with us about Jan on the pod today) released an Apache 2 finetune of Qwen3-4B-thinking, that's focused on SimpleQA.They showed that their tiny model is beating Perplexity Pro on SimpleQA.Alan told us on the pod that Jan (the open source Jan app) is born to be an open source alternative to searching with local models!The trick is, you have to enable some source of search data (Exa, Serper, Tavily) via MCP and then enable tools in Jan, and then.. you have a tiny, completely local perplexity clone with a 4B model!Google drops Gemma 3 270M (blog)In some #breakingNews, Google open sourced a tiny (270M) parameters, "good at instruction following" Gemma variant. This joins models like SmolLM and LFM2 in the "smol models" arena, being only 300MB, you can run this.. on a toaster. This one apparently also fine-tunes very well while being very energy efficient!Big Companies (AKA OpenAI corner this past 2 weeks)Ok ok, we're finally here, a week with GPT-5! ...
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