Restar Stock Surges 487% on AI Demand, Bloom Energy Targets Data Centers

Restar shares have surged on strong AI data center demand, with the company reporting a 487% year-over-year jump in Q1 operating profit and raising its full-year guidance. The stock closed at ¥5,690 with a one-year return of 121.03%, though analysts estimate fair value at around ¥2,588, raising questions about whether the valuation is stretched.

Bloom Energy is targeting AI data center power needs with its new 800V DC-native fuel cell systems, promising cost savings and faster deployment. The company has nearly 1.4 GW already deployed and has partnerships with Oracle and Brookfield. Analysts have modeled potential revenue reaching about US$17.8 billion by 2029, and Bloom Energy has confirmed inclusion in the S&P 500 in September 2026.

Fed Chair Kevin Warsh linked rising long-term yields partly to AI hyperscalers issuing bonds, with the group having issued $121 billion in bonds last year. Warsh also cited economic growth and the Iran war as contributing factors. The Federal Reserve has created an internal AI task force due to report by year end.

Australia has launched a public consultation on AI standards and data center rules, covering energy and water usage requirements as well as community engagement. Submissions are open until 9 October 2026. Separately, the government is seeking public feedback on AI training and infrastructure, with a focus on keeping Australia competitive in AI innovation.

On the research front, IonQ earned four Best Paper Awards for work using generative AI to write quantum optimization circuits, a joint study with Oak Ridge and NVIDIA that could help customers tackle larger quantum problems. Microsoft released four free AI and data science courses on GitHub, covering topics from machine learning to generative AI. Brookhaven National Laboratory is leading a $14.2 million DOE project to build an AI system for the electric grid, aiming to simulate one billion scenarios in 24 hours.

Key Takeaways

  • Restar reported a 487% year-over-year increase in Q1 operating profit driven by AI data center demand, but analysts estimate fair value at around ¥2,588 versus its current ¥5,690 close.
  • Bloom Energy's 800V fuel cell systems target AI data centers, with potential revenue modeled at about US$17.8 billion by 2029 and nearly 1.4 GW already deployed.
  • AI hyperscalers issued $121 billion in bonds last year, contributing to rising long-term yields according to Fed Chair Kevin Warsh.
  • Australia launched a public consultation on AI standards and data center rules, with submissions open until 9 October 2026.
  • IonQ, Oak Ridge, and NVIDIA jointly developed AI-written quantum circuits that could reduce trial and error in quantum computing applications.
  • Microsoft released four free AI and data science courses on GitHub, covering machine learning, neural networks, deep learning, and ethics.
  • Brookhaven National Laboratory leads a $14.2 million DOE project to build an AI system capable of simulating one billion grid scenarios in 24 hours.
  • Investors are turning to quantum computing stocks including IBM, Microsoft, Alphabet, and Intel as an alternative to AI stocks.
  • Ave AI integrated with the Arc blockchain ahead of its Public Mainnet launch on September 16, 2026, supporting cross-chain swaps and on-chain trading.
  • Ave AI's Arc blockchain integration supports market data, asset information, and trading for Arc ecosystem assets.

Restar shares surge on AI demand but valuation questioned

Restar (TSE:3156) closed at ¥5,690 after strong gains including a 1-year return of 121.03%. Q1 FY3/27 results showed operating profit growth of 487% year over year, driven by AI data center demand. Analysts estimate fair value at around ¥2,588, suggesting the stock may be overvalued. The company raised its FY guidance and dividend per share due to strong order visibility.

Bloom Energy's 800V fuel cell systems aim to power AI data centers

Bloom Energy released details on its 800V DC-native fuel cell systems designed for AI data centers, promising cost savings and faster deployment. The company has confirmed inclusion in the S&P 500 in September 2026 and has nearly 1.4 GW already deployed. Partnerships with Oracle and Brookfield support its growth story. Analysts have modeled potential revenue reaching about US$17.8 billion by 2029.

Australia opens public consultation on AI and data center rules

The federal Office of AI launched a public consultation on Friday to help design National AI Standards proposed by Prime Minister Anthony Albanese. The rules will cover data center requirements including energy, water usage, and community engagement. AI training conditions will focus on local investment in talent and research. Submissions are open until 9 October 2026.

Australia seeks public input on AI training and infrastructure future

The Australian Government is asking for public feedback on AI training and large data centers. The consultation process will run for 12 weeks and close on 31 March 2023. The goal is to shape a national AI strategy that keeps Australia at the forefront of AI innovation. The government says AI could transform the economy and improve how Australians live and work.

IonQ explores AI-written quantum circuits with new research

IonQ reported four Best Paper Awards for research using generative AI to write quantum optimization circuits. The joint study with Oak Ridge and NVIDIA removes costly trial and error in testing. AI-written circuits could help customers tackle larger quantum problems without longer run times. The research tightens the link between IonQ hardware plans and real-world applications.

Warsh links AI hyperscaler bond demand to rising borrowing costs

Fed Chair Kevin Warsh said AI hyperscalers issuing bonds are partly pushing up long-term yields. Hyperscalers issued $121 billion in bonds last year. Warsh also cited economic growth and the Iran war as reasons for rising yields. He did not discuss the federal deficit. The Fed has created an internal AI task force due to report by year end.

Microsoft offers free AI and data science courses on GitHub

Microsoft released four free courses on GitHub for students and beginners. The courses cover data science, machine learning, AI, and generative AI. The Machine Learning course has 26 lessons and 52 quizzes using Python and Scikit-learn. The AI course covers neural networks, deep learning, and ethics using TensorFlow and PyTorch. All courses can be done online at your own pace.

Brookhaven Lab leads $14M AI grid project under Genesis Mission

Brookhaven National Laboratory will lead a $14.2 million DOE project to build an AI system for the electric grid. The project aims to simulate one billion grid scenarios in 24 hours. Collaborators include Stony Brook University, New York Power Authority, and National Grid. The funding was announced September 1 by DOE Assistant Secretary Catherine Jereza. The goal is to speed up grid planning and keep power affordable.

Ave.ai integrates Arc blockchain ahead of September 2026 mainnet launch

Ave AI completed its integration with the Arc blockchain ecosystem. The integration supports market data, asset information, and trading for Arc assets. It was done ahead of Arc Public Mainnet's launch on September 16, 2026. Ave AI aims to give traders faster access to emerging assets and liquidity. The platform will offer cross-chain swaps and on-chain trading for Arc ecosystem tokens.

Investors look to quantum computing stocks as AI growth slows

Investors are turning to quantum computing as an alternative to AI stocks. Quantum computing uses superposition and entanglement for faster calculations. Four leading quantum stocks recommended are IBM, Microsoft, Alphabet, and Intel. All four companies have strong portfolios and significant investments in quantum research and development. These stocks are seen as ways to invest in the future of computing.

BENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs

Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules change quickly, evidence is fragmented, and decisions depend on transaction state, participant role, region, and payment rail. Existing benchmarks do not isolate whethe

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