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Daily Digest #469
Want to get in front of 100k AI enthusiasts? Work with us here64†
Hello folks, next week we have two amazing workshops lined up.
On Tuesday: Automating work and streamlining productivity223 with Max from Gumloop.
On Wednesday: How to repurpose content using AI185 with Barbara from Startup Cookie.
Here’s what we have today;
New tutorials:
Use AI to do podcast guest research192 with Zapier and Podscan.
How to prepare, interview, and evaluate for senior leadership roles.261
Create full-time, part-time, and contractor employment agreements116 with ChatGPT.
Speed up web research by generating summaries of web pages229 using AI.
Build an intelligent email reply system138 using Zapier and OpenAI.
Google climbs to the top of AI leaderboards. A new experimental version of Gemini 1.5 Pro675 now ranks #1 on the LMsys leaderboard with a huge lead over GPT-4o. We don’t have scores on traditional benchmarks yet, but the initial impressions from Twitterverse are positive. It’s available on Google’s AI studio and Gemini API to test.
Also, starting August 12, Gemini 1.5 Flash’s base pricing110 will match that of GPT-4o-mini.
GitHub is adding an AI playground to its platform.418 GitHub Models comes with open models like Llama and Mistral and closed ones like GPT-4o and 4o mini from OpenAI. The limited public beta is open for signups now.🍿Our Summary3 (also below)
Enhance RAG response quality with better data preparation495. Unstructured data is notoriously hard to wrangle, but AI systems are hungry for it. Parse, de-identify, chunk, and embed clean, normalized data from any file format for your vector store with Tonic Textual for better quality RAG systems. (sponsor)
Wordware353 (YC S24) gives non-technical domain experts an IDE + toolkit to build AI apps and workflows with natural language. Try it out with promo code LAUNCH (I’m an investor).
Toby272† - Live speech translation on any video call.
Martin367 - Your AI butler with calendar, email, search and more.
TorchChat140 - Run PyTorch LLMs locally on servers, desktop and mobile.
Trudo AI232† - Python-based workflow builder with AI copilot.
Eduwiz277 - Write magical paperwork in a few seconds for free.
LangGraph Studio by LangChain214† - Visualize, interact with, and debug complex agent-based applications.
Workflows by LlamaIndex226 - Event-driven approach to building multi-agent applications.
Clarity283 - Use AI to supercharge founder-led sales.
View more →120
Google Chrome to get 3 new AI features190: Search with Google Lens on Desktop, Gemini-assisted lookup for browsing history and Tab Compare to judge products across multiple tabs.
Microsoft adds OpenAI to its list of competitors in AI and search97 in its latest annual report.
Websites are blocking the wrong AI scrapers156 (because AI companies keep making new ones).
Google Cloud and YC partner76 to give startups a dedicated cluster of Nvidia GPUs.
Suno and Udio are choosing offence168 in the copyright lawsuit by record labels.
a16z is leading a $31M seed in Black Forest Labs162, founders include OG Stable Diffusion creators.
Speaking with two different AIs166† - One’s enthusiastic, another’s cautious.
AI will fundamentally change sales workflows258, with multimodal data and automation being key levers.
Can an AI make a data-driven, visual story?214 One of the rare posts where the team gave AI a fair chance and judged its performance on various parts of the process.
How to use Meta’s SAM 2144 for video segmentation.
GitHub's giving its 100 million+ users a shiny new AI toy to play with. It’s adding an AI playground418 to its platform. Think of it as your personal AI sandbox, right where you already store your code.
What's going on here?
GitHub's rolling out "GitHub Models," letting developers test-drive various AI models directly on their platform.

What does this mean?
At the core of GitHub Models is a nifty playground to test prompts and fiddle with parameters, all for free.
If you dig what you see, you can seamlessly move to coding with these models in Codespaces or VS Code. And if you're ready for the big leagues, there's a clear path to deploy via Azure too. GitHub promises your prompts and outputs won't be shared or used to train the models.
You can tinker with big-name models like GPT-4o, Llama 3.1, and Mistral Large 2 right on GitHub in the limited beta. More language, vision, and other models are in the pipeline as they gear up for general availability.
Why should I care?
GitHub wants to keep "AI engineers" (software engineers using AI APIs) on their platform. Many are shifting to tools like Replit and Cursor, but GitHub wants to offer native AI access to make their Copilot offering more appealing.
Testing multiple models in one place is a big ask from AI engineers, and entire startups are being built to tackle this. GitHub's current lineup doesn't quite cut it for me though—I'd love to see top models from Anthropic, Google, and OpenAI side-by-side. The current option feels like single-party elections 🫣.
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