🤖🦾 Ultra-Fast Data Compression, AI Factories, and The Bitter Lesson

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ZeroPoint Technologies: Shaping the Future of Ultra-Fast, Hardware-Based Data Compression

Data centers are the backbone of our digital world. As the demand for compute skyrockets, so does the need to store and retrieve data efficiently, not only for streaming high-definition videos but also for training the latest AI models.

Currently, data centers consume about 2% of global electricity, with projections suggesting this could be 5x by 2030. Despite the push for renewables, managing the rising energy costs remains a challenge. But what if you could remove up to 70% of unnecessary data and thereby boost performance per watt by up to 50%?

ZeroPoint Technologies pioneers hardware-based data compression that can increase memory capacity by 2-4x and reduce the total cost of ownership for servers by up to 25%. Founded in 2016 by Per Stenström and Angelos Arelakis, it recently closed a €5.0M Series A, led by Matterwave Ventures, and joined by Industrifonden, Climentum Capital, and Chalmers Ventures

Learn more about the future of ultra-fast, hardware-based data compression from our interview with the CEO, Klas Moreau

Future of Computing News

🔬 Linear accelerators could turbocharge EUV lithography: Is the Future of Moore’s Law in a Particle Accelerator? (IEEE Spectrum)

🦾 “Build, maintain, and operate” AWS’ cloud data center cluster in the Frankfurt metropolitan area: Amazon to spend €10B on expanding its cloud and logistics operations in Germany (SiliconAngle)

⚛️🧱 Generative Chemistry and Accelerated DFT: Introducing two powerful new capabilities in Azure Quantum Elements (Microsoft)

Funding News

Good Reads

Life's short. Build something important: https://www.buildlist.xyz/

“Companies and countries are partnering with NVIDIA to shift the trillion-dollar installed base of traditional data centers to accelerated computing and build a new type of data center, AI factories, to produce a new commodity, artificial intelligence.”

“Granting foundation models ‘search’ (the ability to think for longer) might upend Scaling Laws and change AI’s trajectory.”

“The biggest lesson that can be read from 70 years of AI research is that general methods that leverage computation are ultimately the most effective, and by a large margin.”

“Extensive experiments demonstrate MCTSr’s efficacy in solving Olympiad-level mathematical problems, significantly improving success rates across multiple datasets, including GSM8K, GSM Hard, MATH, and Olympiad-level benchmarks, including Math Odyssey, AIME, and OlympiadBench.”

Free book by Chris Ferrie, a Canadian physicist

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