🥴EU’s Delulu Chip Plan Falls Flat

Today we will discuss:

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• EU’s chip plan faces cold reality—A new audit warns that the EU’s 2030 semiconductor targets are far from attainable, with funding issues and global competition undermining progress

• Don’t miss this week’s Workflow Wednesday—AI learning that sticks, sharpen your prompting skills with LearnPrompting.org, use Jenni AI as your research + writing assistant, and automate your AI-powered reading list with Notion, Zapier, and ChatGPT; now available at only $20/month! 

• Alibaba’s Qwen3—Qwen3 outperforms DeepSeek’s R1, setting new benchmarks in open-source AI

• In other AI news today—Hugging Face unveils a $100 3D-printed robotic arm, OpenAI adds shopping features to ChatGPT’s search, UPS explores deploying humanoid robots with Figure AI, and Congress passes a bill targeting deepfake nudes and revenge porn

• Saved the best for last—8 must-try AI tools

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EU’s microchip dreams face harsh reality check in scathing new audit

Key Points 

• The EU’s 20% global chip market target by 2030 is “aspirational” and far from achievable, auditors say.

• Fragmented funding and lack of technical expertise are stalling Europe’s ability to scale chip production.

• Geopolitical risks and soaring chip demand make Europe’s reliance on foreign suppliers a growing vulnerability. 

☕News - A new report from the European Court of Auditors (ECA) has sharply criticized the EU’s plan to become a global microchip powerhouse, calling its 2030 goal "deeply disconnected from reality." 

The EU had aimed to supply 20% of the world’s semiconductors by the end of the decade, reflecting the percentage of end users in Europe, but the ECA says the plan is more ambition than action.

🫠Too little, too fragmented - Despite major players like Intel and Samsung having a presence in Europe, the ECA argues that fragmented tax regimes and scattered funding are blocking real progress. 

“We are competing in a global race, but from the back of the field,” said audit lead Annemie Turtelboom. She warned that the bloc lacks the financial coordination and technical know-how to scale up fast enough.

🌍Geopolitical risks & soaring demand - The report also flags growing geopolitical instability. With Donald Trump hinting at tariffs on chip imports and China set to overtake Taiwan as the top chipmaker by 2030, the EU’s dependence on foreign suppliers could become a major vulnerability, especially with booming demand from defense, AI, and green tech.

🥸A critical component in crisis - Chips are now central to everything from smartphones to cars, with modern vehicles using over 1,500 chips and that number expected to double by 2030. While the 2022 EU Chips Act gave the sector a regulatory boost, the ECA says far more is needed to keep pace in a fast-moving global market.

Read the full story here. 

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Alibaba’s Qwen3 recognized as a breakthrough, surpassing DeepSeek’s R1 performance

Key Points 

• Alibaba's Qwen3 series features eight variations, hybrid reasoning, and multilingual support in 119 languages.

• Qwen3’s mixture of experts (MoE) architecture boosts computational efficiency, significantly reducing deployment costs for developers.

👨‍💻News - Alibaba unveiled its next-generation open-source large language models (LLMs), Qwen3, marking a significant development in China’s rapidly growing AI scene. 

The company’s latest release is already being hailed as a breakthrough, with Qwen3 outperforming rivals like DeepSeek’s R1 in several key benchmarks.

🦸‍♂️Improved performance & flexibility - Qwen3 brings improvements in reasoning, instruction-following, tool usage, and multilingual capabilities. The series includes eight variations of different sizes and architectures, giving developers flexibility to build AI applications for devices such as mobile phones. 

One of the standout features is its hybrid reasoning model, which allows the model to seamlessly switch between a “thinking mode” for complex tasks like coding and a “non-thinking mode” for quicker, general responses.

🤓What’s more? Some versions of Qwen3 adopt a mixture of experts (MoE) architecture, which improves computational efficiency. MoE models break tasks down into subtasks, with specialized submodels handling each one. The Qwen3-235B-A22B MoE model, for example, significantly reduces deployment costs, making high-performance AI more accessible

Read the full story here.