💡 What are the nerds up to?
➜ Do Developers Hate Their Jobs? According to a new Stack Overflow survey, software engineers globally embrace AI. As much as 72% of respondents are in favor of leveraging AI tools in their daily work and 81% of them cite increased productivity as the main benefit. What’s more, 70% of developers don’t worry about losing their jobs to AI. However, it turns out that 4 in 5 respondents are unhappy. Main factors include dealing with technical debt, complexity of tech stacks, and reliability of the systems they work with. Experts also point to stress and uncertainty caused by the recent massive layoffs.
Shiftmag
➜ How to Run Llama on Home Devices? Thanks to Distributed Llama, it’s now possible to run huge LLMs across multiple home devices. All it takes is an AI cluster! Distributed Llama leverages tensor parallism and is optimized for the low amount of data required for synchronization.
Medium
➜ Building Custom AI Agents When You’re Not a Geek. A new tool on the block, Wordware, has just launched their IDE platform for building AI agents which allows domain experts to create custom content generation models, invoice processing, data querying, reporting, and sales enrichment using an LLM backend, without the need to know how to code.
Product Hunt
➜ New Copilot, But Better? Built to make engineers ‘extraordinarily productive’, Cursor looks a lot like GitHub Copilot, with pretty much the same functionality. I’m hearing more and more stories from developers praising Cursor and saying it works much better than the predecessor.
Cursor
➜ Gemini 1.5 Pro Beats GPT-4. Have you seen Google AI Studio? A 2 million token context window, improved customization, effortless model tuning capabilities, the ability to add video, and code execution (so you can sit back while the tool creates charts from your data) – word is Gemini 1.5 Pro is much better than GPT-4.
Google AI Studio
➜ AI Is Not Overhyped. Now here’s a developer voice with a clear argument. A great longer read on how to make the most of LLMs in the world of engineering by Google DeepMind’s Nicholas Carlini. “I would say I’m at least 50% faster at writing code for both my research projects and my side projects as a result of these models,” claims Nicholas.
Nicholas Carlini’s blog