LangChain Terminal Agent for Secure Shell Execution

We are moving from information retrieval to knowledge synthesis. Tools like NotebookLM show how long-context AI can augment human cognition rather than replace it. I explored the technical, cognitive, and workflow impact of this shift, including RAG, multimodal context, and second-brain systems. This may define the next phase of AI adoption.

We talk so much about AI, when the intelligence of a computer doesn't even reach a tenth of a baby's intelligence. We train Large Language Models like Gemini with a very large dataset, actually the whole internet, yet a baby's mind can comprehend who is to be trusted by just a few snapshots of his surroundings. We shouldn't mistake intelligence for knowing everything and being able to perform tasks as a result of knowledge. Intelligence is what initializes the process, and that only comes from human beings.

I shipped a production-ready authentication flow in 22 minutes today. The secret isn't better prompts; it's using natural language to define the state machine first. Let the AI handle the boilerplate while you focus on the logic flow. Vibecoding is just extreme modularity at the speed of thought. Would you do this?

Our AlphaProof paper is in this week’s issue of Nature Magazine! In 2024, Google DeepMind's proof agents AlphaProof & AlphaGeometry together made a substantial leap in AI by achieving the silver-medal standard in solving IMO problems. The Nature paper describes the technical innovations required—in particular, the RL loop bridging natural language & symbolic rigor—that made AlphaProof possible. Read our Nature paper: https://lnkd.in/epDQSn2i Read our IMO 2024 blog: https://lnkd.in/eBei2ZUb

AI is no longer just answering questions. It’s starting to think with us. 🧠⚡ NotebookLM + long-context LLMs may change how humans read, learn, and create knowledge. Read here: https://lnkd.in/djgpAAEC #AI #NotebookLM #FutureTech

AI is no longer just answering questions. It’s starting to think with us. 🧠⚡ NotebookLM + long-context LLMs may change how humans read, learn, and create knowledge. Read here: https://lnkd.in/djgpAAEC #AI #NotebookLM #FutureTech

Most people still use AI to ask questions. The real power is using AI to think. 🧠🔥 NotebookLM shows what knowledge engines will look like. Full article: https://lnkd.in/djgpAAEC #ArtificialIntelligence #SecondBrain #LLM

𝗧𝗵𝗶𝘀 𝗔𝗜 𝗣𝗮𝗽𝗲𝗿 𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲𝘀 𝗧𝗶𝗻𝘆𝗟𝗼𝗥𝗔, 𝗔 𝟭𝟯-𝗣𝗮𝗿𝗮𝗺𝗲𝘁𝗲𝗿 𝗙𝗶𝗻𝗲-𝗧𝘂𝗻𝗶𝗻𝗴 𝗠𝗲𝘁𝗵𝗼𝗱 𝗧𝗵𝗮𝘁 𝗥𝗲𝗮𝗰𝗵𝗲𝘀 𝟵𝟭.𝟴 𝗣𝗲𝗿𝗰𝗲𝗻𝘁 𝗚𝗦𝗠𝟴𝗞 𝗼𝗻 𝗤𝘄𝗲𝗻𝟮.𝟱-𝟳𝗕 Researchers from FAIR at Meta, Cornell University, and Carnegie Mellon University have demonstrated that large language models (LLMs) can learn to reason using a remarkably small number of trained parameters. The research team introduces TinyLoRA, a parameterization that can scale down to a single trainable parameter under extreme sharing settings. Using this method on a […] The post This AI Paper Introduces TinyLoRA, A 13-Parameter Fine-Tuning Method That Reaches 91.8 Percent GSM8K on Qwen2.5-7B appeared first on MarkTechPost. https://lnkd.in/epRhtVws

AI is no longer just answering questions. It’s starting to think with us. 🧠⚡ NotebookLM + long-context LLMs may change how humans read, learn, and create knowledge. Read here: https://smpl.is/ai6it #AI #NotebookLM #FutureTech

But pundits told me LLMs were not stochastic parrots. How is this possible? And do not make me rant about language in LLMs. That's something that is virtually absent in most of the AI conversations. Everyone is obsessed with reasoning and takes language for granted. The follow-up paper should be: "The illusion of language