Mike Groseclose

A lot of people are switching from ChatGPT to Claude lately and not always for the right reasons. For many, the move is driven more by politics (mutual dislike for Trump and US Defense) than product. That's understandable (given the war situation they have created), but it's not a great way to pick your tools. Before you go all-in on either platform, here's an honest breakdown of where each one actually excels: 𝗪𝗵𝗲𝗿𝗲 𝗖𝗹𝗮𝘂𝗱𝗲 𝘄𝗶𝗻𝘀: Claude is the best coding AI available right now. Period. Their Opus models are in a league of their own, with OpenAI's Codex a distant second. If your primary use case is coding, Claude (and specifically Claude Code) should be your go-to. Claude Code also handles non-coding agentic tasks surprisingly well like making presentations, editing spreadsheets, organizing messy file systems, automating workflows via MCPs, extracting data from PDFs, even scheduling recurring tasks to name a few. For this reason, i prefer to use it in OpenClaw too. And to add to that, The Claude Cowork UI makes all of this easy for users who don't like a terminal. One more thing I appreciate: Claude is less sycophantic and writes in a more natural, human tone. I use it regularly to rewrite copy. 𝗪𝗵𝗲𝗿𝗲 𝗖𝗵𝗮𝘁𝗚𝗣𝗧 𝘄𝗶𝗻𝘀: Claude's thinking model is its weakest link. It often doesn't reason deeply enough, which leads to more hallucinations. By contrast, ChatGPT's thinking model (available in the paid version, please don’t use the free tier) is the most reliable AI I've used. In six months, I haven't caught it hallucinating once. For everyday queries, health questions, research, current events, regular research and deep research, ChatGPT Thinking model is my pick. Claude consistently underperforms in these areas. 𝗠𝘆 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱𝗮𝘁𝗶𝗼𝗻: Subscribe to paid versions of both. Use each for what it's best at. 𝗪𝗵𝗮𝘁 𝗮𝗯𝗼𝘂𝘁 𝗚𝗼𝗼𝗴𝗹𝗲: Gemini's consumer products are disappointing. Oddly, their APIs perform significantly better, and Nano Banana and Google AI Studio are the only Google AI products I'd actually recommend. The underlying models may be strong, but the product layer needs some serious work.

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Big news for Meta Neural Band owners! 🎉 Starting this week, we're rolling out a groundbreaking new way to message: writing with your finger on any surface (https://lnkd.in/g6t_9sPC). Imagine messaging as simply as you wrote in elementary school—no keyboards, no accessories, just you and the neural band. This isn't just a new feature; it's a fundamental step in the evolution of human-computer interaction. The neural band natively understands written text using human biology (EMG at the wrist), eliminating the need for users to learn a new interface (physical/virtual keyboards, touch screen UIs or mice). This is a new step in the paradigm shift from humans adapting to computers to computers communicating like humans. While much of the recent AI focus has been on language models and reasoning, the same underlying techniques have been taking perceptive AI to quite a mature level over the last 10 years. First it revolutionized computer vision (https://lnkd.in/gejhZ9Vu) and speech recognition (ASR, TTS). Beyond human senses, it enabled the processing of complex sensor suites that made applications like self driving cars possible (https://lnkd.in/ghxE2hvR). When we launched the Neural Band last fall (https://lnkd.in/gyuzRVeD), we proved for the first time that a consumer-grade device could accurately capture and process neural activations. Initial gestures were innovative, but handwriting is different. While finger differentiated taps and swipes could have arguably been implemented using other modalities, the richness and accuracy of the signal required for handwriting requires the high-information-entropy bandwidth unique to an EMG-based device. I can't wait for many of you to experience the "waouh, this is new!" feeling for yourself. While this is the culmination of 10 years of research (https://lnkd.in/gxm_gc3z), we're just getting started! Stay tuned for the even more exciting, next-level capabilities we are working on. #MetaNeuralBand #HumanComputerInteraction #PerceptiveAI #Innovation #EMG

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