Augmented Systems LLP’s Post

🎙️ New Episode Alert! #017 - Reasoning with AI: Noam Brown’s Insights and the Revolutionary o1 Model In this episode, we explore AI researcher Noam Brown's trailblazing work on reasoning in AI and the development of the o1 model. Brown makes a compelling case for the importance of search and planning in AI, a shift from traditional instant-action models. These techniques have fueled superhuman performance in complex games like poker and Go—and now, the o1 model takes this further. Episode Highlights: 🔍 AI in Games: Poker and Go Discover how search and planning strategies have led to breakthroughs in AI performance. 🌐 The Revolutionary o1 Model Learn how o1 uses reinforcement learning to craft optimized chains of thought for sophisticated reasoning. 🚀 Performance Across Domains Explore o1’s impressive results in areas like AIME tests, competitive coding, and scientific research. 🌎 Redefining AI’s Future Brown envisions a future where AI moves beyond chatbots to tackle high-value problems in scientific discovery and technological innovation. 🤖 A Call to Action Brown encourages AI researchers to shift focus toward impactful, long-term advancements in AI capabilities. 🎧 Ready to dive into the potential of reasoning and compute in AI? Listen to Episode #017 now! https://lnkd.in/gz3YvraN #AI #ReinforcementLearning #NoamBrown #LLMs #TechInnovation #ArtificialIntelligence

"Are we there yet?" Listen to Y Combinator's eagle-eye view rather than "the word from the herd" - A year is a long time in AI: "...it's hard to even remember now but a year ago one of the things that people said a lot was that these LLMs are not reliable enough to deploy in the Enterprise they hallucinate... [but now] not only is it translating into real Revenue but translating into real deployments that are being used at Large Scale ...because we've learned how to make the agents reliable via the kinds of techniques that Jake talked about when he was here and all this infrastructure has grown up around the models, it's enabled people to make them reliable. https://lnkd.in/dhtMdgQk #agents #llm #ai

I'm thrilled to share a new blog post that delves into the future of AI, featuring an exclusive interview with Jonathan Ross. This in-depth discussion covers the latest advancements in AI, including insights on GPT-6, the role of smaller models, and the competitive landscape between OpenAI and Google. Discover how these developments are shaping the industry, what opportunities lie ahead for startups, and the potential impacts on various sectors. Whether you're an AI enthusiast, a tech innovator, or simply curious about the future, this post is a must-read.🔗  Read the full post here: https://lnkd.in/dzBxQK6T Join the conversation and let's explore the transformative impact of AI together #AI #FutureOfAI #TechInnovation Feel free to share your thoughts or insights in the comments below 🤖💡

Top 10 Data Science Startups in USA https://lnkd.in/gHGNVVtq Discover the top 10 data science startups in the USA driving innovation with AI, machine learning, and analytics! See who's shaping the future of tech. #DataScienceStartupsinUSA #DataScienceStartups #Top10DataScienceStartups #DataScience #10DataScienceStartups #AINews #AnalyticsInsight #AnalyticsInsightMagazine

Please media types writing about the cost of AI: recognize there is a difference between huge GPU/TPU clusters needed to train foundation models vs. inference costs to run most apps on top of foundation models. The two are not synonymous, so you can dial back some of the doom and gloom about AI startups and your commingling of the two different AI business types.

Builders transform the world by turning curiosity into action, learning into growth, and ideas into shared progress. 🚀 Here are the top 5 things builders have been exploring this past week📰: 1. MIT Technology Review - How OpenAI stress-tests its models: https://lnkd.in/gRSMbKcb (credit: Julian Bright) 2. Amigo.ai - The Future of Expertise: https://lnkd.in/g-vbMJP3 (credit: Julian Bright) 3. Flexible LLM Guardrail Development - A new applied AI paper from govtechsg: https://lnkd.in/gzgfnhhE (credit: Gabriel Chua) 4. QwQ 32B Preview - Experimental research model focused on advanced AI reasoning by Qwen: https://lnkd.in/gaAJHDtG  (credit: Julian Bright) 5. Menlo Ventures - The State of Generative AI in Enterprise: https://lnkd.in/grj-_bYD (credit: Annie Liao 🇦🇺) What are your thoughts on these? Let us know below! 👇 #AI #startups #builders #genAI #innovation

📹 You need to watch this video. ✨ New doja picks. Where we share with you the industry knowledge you should be keeping up with ✨ This video highlights the need for startups to have a clear mission to maintain a competitive edge within AI 🚀

Grok-2 Takes xAI to New Heights, Outperforming GPT-4 and Claude! Grok-2, now available in beta on the X platform, has achieved state-of-the-art performance, outperforming major competitors like Anthropic’s Claude and OpenAI’s GPT-4 in key areas. This marks a pivotal moment for the startup, which initially launched Grok-1 as a niche, no-filter chatbot. This development positions xAI as a serious contender in the AI industry, offering a model that not only excels in technical benchmarks but also has practical applications ready for enterprise use. With the upcoming release of an enterprise API, xAI is set to attract significant interest from businesses seeking cutting-edge AI solutions. The startup’s access to vast real-time data from X and its ability to draw top-tier talent under Elon Musk’s leadership further solidify its potential for rapid growth and long-term success in the competitive AI market.

AI: Tackling Overfitting in Small Datasets 🚨 Problem: Overfitting is a major issue when working with small datasets in AI, leading to poor performance on new data. 💡 Solution: Apply Dropout Regularization, which randomly drops units during training to prevent overfitting. 🧑💻 Code: tf.keras.layers.Dropout(0.5) By introducing Dropout layers, you ensure your model generalizes better without relying too much on specific nodes. This is key when data is limited! 📊🔑 #AI #MachineLearning #DeepLearning #SmallDataSets #OverfittingSolution #DropoutRegularization #TechTips #AIResearch #DataScience #founders #startups

Check out this one from Veksel Consulting & Contracting