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Article URL: https://blog.google/products/search/google-search-ai-mode-update/

Comments URL: https://news.ycombinator.com/item?id=44044073

Points: 2

# Comments: 0

Article URL: https://deepmind.google/models/imagen/

Comments URL: https://news.ycombinator.com/item?id=44044063

Points: 2

# Comments: 0

The pricey new Google AI Ultra also comes with a huge amount of cloud storage and a ton of other features.

Android XR head Shahram Izadi talked to CNET about Google's big next steps for AI, AR and VR, and the company's partnerships with Samsung, Warby Parker and Xreal.

At Google I/O today, the tech giant debuted a brand new AI filmmaking tool. But the price tag might be a deal-breaker.

Gemini in Chrome can do a lot more than summarize a web page for you.

The new AI Mode also lets you ask Gemini to help find exactly what you're looking for.

Two CNET editors tested Ninja's latest air fryer, and we're calling it a top-tier pick for quick, crispy eats.

Google Beam uses an AI model that turns video calls into a lifelike 3D experience. It could be the next best thing to being there.

Want to optimize your kidney health? Try adding these foods to your diet.

Orkes has made the Conductor MCP Server public which is compatible with both OSS Conductor and Orkes Conductor endpoints.

For those who don't know, Conductor is an open source workflow orchestration tool: https://github.com/conductor-oss/conductor

Orkes Conductor is a modern enterprise platform built around that tool: https://orkes.io/

Check out the repo here: https://github.com/conductor-oss/conductor-mcp

Comments URL: https://news.ycombinator.com/item?id=44043637

Points: 1

# Comments: 0

Article URL: https://aembit.io/blog/mcp-oauth-2-1-pkce-and-the-future-of-ai-authorization/

Comments URL: https://news.ycombinator.com/item?id=44043629

Points: 1

# Comments: 0

I've built an open-source implementation of Google DeepMind's AlphaEvolve system called OpenEvolve. It's an evolutionary coding agent that uses LLMs to discover and optimize algorithms through iterative evolution.

Try it out: https://github.com/codelion/openevolve

What is this?

OpenEvolve evolves entire codebases (not just single functions) by leveraging an ensemble of LLMs combined with automated evaluation. It follows the evolutionary approach described in the AlphaEvolve paper but is fully open source and configurable.

I built this because I wanted to experiment with evolutionary code generation and see if I could replicate DeepMind's results. The original system successfully improved Google's data centers and found new mathematical algorithms, but no implementation was released.

How it works

The system has four main components that work together in an evolutionary loop:

1. Program Database: Stores programs and their metrics in a MAP-Elites inspired structure 2. Prompt Sampler: Creates context-rich prompts with past solutions 3. LLM Ensemble: Generates code modifications using multiple models 4. Evaluator Pool: Tests programs and provides feedback metrics

What you can do with it

- Run existing examples to see evolution in action - Define your own problems with custom evaluation functions - Configure LLM backends (works with any OpenAI-compatible API) - Use multiple LLMs in ensemble for better results - Optimize algorithms with multiple objectives

Two examples I've replicated from the AlphaEvolve paper:

- Circle Packing: Evolved from simple geometric patterns to sophisticated mathematical optimization, reaching 99.97% of DeepMind's reported results (2.634 vs 2.635 sum of radii for n=26). - Function Minimization: Transformed a random search into a complete simulated annealing algorithm with cooling schedules and adaptive step sizes.

Technical insights

- Low latency LLMs are critical for rapid generation cycles - Best results using Gemini-Flash-2.0-lite + Gemini-Flash-2.0 as the ensemble - For the circle packing problem, Gemini-Flash-2.0 + Claude-Sonnet-3.7 performed best - Cerebras AI's API provided the fastest inference speeds - Two-phase approach (exploration then exploitation) worked best for complex problems

Getting started (takes < 2 minutes)

# Clone and install git clone https://github.com/codelion/openevolve.git cd openevolve pip install -e .

# Run the function minimization example python openevolve-run.py examples/function_minimization/initial_program.py \ examples/function_minimization/evaluator.py \ --config examples/function_minimization/config.yaml \ --iterations 50

All you need is Python 3.9+ and an API key for an LLM service. Configuration is done through simple YAML files.

I'll be around to answer questions and discuss!

Comments URL: https://news.ycombinator.com/item?id=44043625

Points: 1

# Comments: 0

Article URL: https://www.youtube.com/watch?v=o8NiE3XMPrM

Comments URL: https://news.ycombinator.com/item?id=44043618

Points: 3

# Comments: 0

Article URL: https://www.bloomberg.com/news/articles/2025-05-20/doordash-ends-ai-voice-ordering-product-for-restaurants

Comments URL: https://news.ycombinator.com/item?id=44043609

Points: 1

# Comments: 1

Article URL: https://blog.runreveal.com/introducing-pipelines-in-runreveal/

Comments URL: https://news.ycombinator.com/item?id=44043607

Points: 1

# Comments: 0

The true mistake is not learning from your own mistakes.

My platform helps you avoid that with Mistakes Tracking, Prevention Center, Advanced Analytics, and more ... to learn from your own mistakes. Designed with first principles thinking in mind.

Comments URL: https://news.ycombinator.com/item?id=44043604

Points: 1

# Comments: 0

Article URL: https://anephenix.com/blog/post/introducing-event-emitter

Comments URL: https://news.ycombinator.com/item?id=44043603

Points: 1

# Comments: 0

Article URL: https://www.youtube.com/watch?v=HsAatv08e9U

Comments URL: https://news.ycombinator.com/item?id=44043601

Points: 2

# Comments: 0