Weights & Biases’ Post

Since last week's launch, our inboxes have been flooded with your stories. While the details vary, the core frustration is identical. You need to better understand your tech stack so you can do something important—build a new feature, find a bug, integrate a product into the enterprise, modernize your full tech infrastructure. But the blocker between you and that goal is a time-consuming, expensive, and maddening technical discovery process that gets in the way every single time. Today, we thought we'd share our own story. Here's what we experienced, and discovered, that led us to founding Driver AI. https://lnkd.in/g7BgEVJG

From Algorithms to Insights: Navigating the Future with BrowserStack In this enlightening session, we’ll delve into how AI can revolutionize software quality, decode the challenges faced by engineering teams worldwide, and guide you on leveraging AI to enhance your quality strategies. Join us as we explore the intersection of artificial intelligence and quality engineering! With Tom Holmes & Charlie Lee https://lnkd.in/dz5ekhV9

Ever wondered how the future of debugging looks amidst the rapid evolution of AI? We've just explored the cutting-edge tools that are not only shaping but also revolutionizing the way we approach software errors in 2024. From intelligent assistants to predictive analytics and automated code repair, our latest blog dives into how AI is transforming debugging from a daunting task into an innovative collaboration . Whether you're a seasoned developer or just curious about the tech landscape, these insights are bound to spark your interest!
 Check out our blog for a closer look: https://buff.ly/3UPy70x #AItools #codercommunity #techblog #debuggingwithAI #AItoolsfordevelopers #instablog #expertblog

Agents are AI teammates that complete tasks on autopilot. 🙌 As an extra pair of hands for your team, they follow the processes and use the software that powers your business. 💡In our latest deep dive, Daniel Palmer covers everything you need to know to get started building Agents with Relevance AI.

⬇️ Beginner's guide to building an AI Agent with Relevance ⬇️

It's been about a month since I got early access to Google's Gemini 1.5 Pro 🦾 Some thoughts: 🗂️ Access to Google Drive is an absolute game-changer No need to fiddle around with custom agents — everything you have saved in Google Drive is immediately accessible, regardless of format. Images, videos, files can all be analyzed within the same chat. This unlocks an incredible amount of productivity. 🔍 Recall and search have never been better Gone are the days of me racking my brain to try and remember a particular quote from a specific user interview — I had Gemini read all of my interview transcripts (hours upon hours of conversations that were saved on Drive) and asked it to find that soundbite based on what I remembered about it. And voilà, Gemini found it for me. Massive brownie points (or what do robots want instead of brownies?). 📝 True wealth is a million tokens I keep having to remind myself that we're still in the early days of AI and I expect larger and larger context windows to be made possible — but holy cannoli, this feels like your first 1 GB flash drive in the era of 3 MB floppy disks (remember those?). Especially when I want Gemini to parse multiple hefty documents scattered across my Drive — which I keep doing! 💡 Gemini has become my second left brain As the LLM arms race continues to rage on, we're starting to see what each of them excel at. What I deeply appreciate about Gemini is how it defaults to pragmatic, analytical outputs; our "conversations" tend to look like a series of analyst reports! This is particularly useful for what I need from my AI at this stage of building (and also happens to be my preferred mode of receiving information right now). Grateful to the Google team for inviting me in to play in the sandbox so early on 🏰 onwards and upwards!

Today we’re introducing four revolutionary product redesigns. A New Latch Data, Workflows, Registry, and Pods. New Data, New Workflows... Are you getting it?! These are not four separate redesigns. We're replacing *the entire platform* with just an AI Chatbot, and we are calling it Latch AI. We see where the future is headed. No more fussing with buttons, tables, or forms. Upload your data files and Latch will figure out the rest. Today, Latch is going to reinvent biology, and take biocomputing into the future it deserves. Check it out at Latch.AI

🚀 Marius Buleandra and I are doing YCombinator with Gustaf Alströmer 🇺🇦 this summer! If 2023 was the year of AI POCs, 2024 is the year of reliability. Hamming is an experimentation platform that helps teams build reliable AI products. We’re starting with automating prompt engineering, evals & observability. We’re adding guardrails & red-teaming soon to help enterprises build production-grade AI apps in weeks. Every company is already an AI company or going to be an AI company in the next few years - reliability is the #1 issue slowing down enterprise AI adoption.

Let us know what you think. And book a demo with us to learn more!

This is an innovative and meaningful use of AI to help bridge the information gap between industry and the public. As a former politician, I know how overwhelming and time-consuming public consultation processes can be, and as a citizen, I know how hard it can be to find accurate, easy-to-understand information about an industrial project and its impacts. I look forward to seeing all the things this tool can do. Brava, Tamara Little and Coast Communications and Public Affairs!