INNOVATION - AI Dynamics

Cursor Developer Habits Report on AI Coding

By

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28 May 2026 17h47

Introducing the Cursor Developer Habits Report.

We’re sharing some of our findings on how software development is changing.

It’s based on the most comprehensive dataset on AI coding in the world, across all model families. pic.twitter.com/c4ZOeVErEO
— Cursor (@cursor_ai) 28 mai 2026

Introducing the Cursor Developer Habits Report. We’re sharing some of our findings on how software development is changing. It’s based on the most comprehensive dataset on AI coding in the world, across all model families.

→ View original post on X — @cursor_ai,

28 May 2026

Wafer-Scale AI Compute: Dedicated Silicon Architecture

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@cerebras

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28 May 2026 16h45

“This technology, this work would be big enough to require dedicated silicon… you needed to start with a clean sheet of paper and you needed to do something fundamentally different.”@andrewdfeldman joined @PeterDiamandis on MOONSHOTS to discuss wafer-scale AI compute, fast… pic.twitter.com/RNv3i2VTZL
— Cerebras (@cerebras) 28 mai 2026

“This technology, this work would be big enough to require dedicated silicon… you needed to start with a clean sheet of paper and you needed to do something fundamentally different.” @andrewdfeldman joined @PeterDiamandis on MOONSHOTS to discuss wafer-scale AI compute, fast

→ View original post on X — @cerebras,

28 May 2026

DiffusionBlocks: Training Neural Networks Block by Block

By

@hardmaru

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28 May 2026 15h47

DiffusionBlocks: Training Neural Networks One Block at a Time

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28 May 2026

AI Solutions for Aerospace, Automotive, Energy, Physics

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@mistralai

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28 May 2026 12h53

We're taking on the hardest problems in the real world Today at The AI Now Summit, held at the Louvre, we announced AI solutions for aerospace, automotive, energy, and physics. Deployed in production at @Airbus , @BMW
, @EDFofficiel , and more. More below:

→ View original post on X — @mistralai,

28 May 2026

Cursor’s frontier model with 100x fewer resources than Google

By

@jxmnop

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28 May 2026 5h46

it is wild that Cursor trained a model closer to the frontier than Google with 100x fewer people and (guessing) ~100x less compute i am surprised this was even possible. also praying for the Gemini comeback ofc

→ View original post on X — @jxmnop,

28 May 2026

Google Gemini 3 Deep Think Advances Scientific Discovery

By

@ronald_vanloon

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28 May 2026 4h24

How Google Is Pushing Scientific Discovery with Gemini 3 Deep Think
by @GoogleDeepMind
#ArtificialIntelligence #MachineLearning #ML pic.twitter.com/zrkVpkdu3k
— Ronald van Loon (@Ronald_vanLoon) 28 mai 2026

How Google Is Pushing Scientific Discovery with Gemini 3 Deep Think
by @GoogleDeepMind #ArtificialIntelligence #MachineLearning #ML

→ View original post on X — @ronald_vanloon,

28 May 2026

Block-by-Block Neural Network Training Framework

By

@sakanaailabs

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28 May 2026 0h38

ニューラルネットワークをブロックごとに学習する枠組みを開発

ブログ: https://t.co/45Xvzl1T1k

ニューラルネットワークの学習は通常、ネットワーク全体を一度に扱う必要があり、深いモデルほど多くのメモリを必要とします。このメモリ消費は、近年のAIモデルの大規模化を支える上で大きな制約と… https://t.co/DhnviMIgPd
— Sakana AI (@SakanaAILabs) 27 mai 2026

Developing a Framework for Learning Neural Networks Block by Block Blog: http://
pub.sakana.ai/diffusionblocks Neural network training typically requires handling the entire network at once, and deeper models demand even more memory. This memory consumption has become a major constraint in

→ View original post on X — @sakanaailabs,

28 May 2026