Artificial Intelligence thread

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tokenanalyst

Lieutenant General
Registered Member

A brand-new optoelectronic fusion AI intelligent computing platform was released.​


In Beijing, Every Moment Deep Thinking, Biren Technology, and Jieyue (StepFun) recently announced a strategic partnership to jointly release an optoelectronic fusion AI intelligent computing platform. The collaboration integrates Biren’s domestic GPU infrastructure, Every Moment Deep Thinking’s spatial optical chip technology, and Jieyue’s large-scale model algorithms into a unified hardware-software ecosystem. Company leadership emphasized that the alliance connects the industry-academia-research chain to accelerate the commercialization of optoelectronic computing solutions. By synchronizing specialized chips with advanced AI frameworks, the platform aims to significantly lower deployment costs for large models while enhancing processing efficiency across both cloud and edge environments.

This initiative directly tackles a major bottleneck in modern AI infrastructure: traditional electronic chips have hit fundamental energy efficiency ceilings due to physical limitations. Optoelectronic integration presents a critical breakthrough by leveraging photonics’ inherent advantages, such as ultra-fast data transmission, low power consumption, and high-capacity parallel processing. Supported by academic expertise from Tsinghua University, the tripartite project specifically addresses the longstanding industry challenge of scaling laboratory-grade photonic technology for reliable mass production. Ultimately, this collaboration establishes a scalable, energy-efficient computing foundation designed to overcome legacy hardware constraints and drive the practical advancement of next-generation AI infrastructure.

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Topazchen

Junior Member
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siegecrossbow said:
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https://twitter.com/i/web/status/2076957440109625718

"The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organisation, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives. Funding would need to be substantial and likely mostly come from industry, in order to attract world-class technical talent and provide the necessary compute resources for large-scale testing.
The Standards Body would be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security. A model would qualify as ‘Frontier-class’ if it meets certain thresholds on a set of benchmarks determined by the Standards Body and regularly updated to keep pace with evolving AI capabilities. Organisations with ‘Frontier Models’ as defined by those benchmarks would be deemed ‘Frontier Labs’, and be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research, and more.
Initially, Frontier Labs would voluntarily share models with the Standards Body for review up to 30 days before release. Once the assessment protocol is shown to be effective and robust, formalisation could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market. Labs would also work with the Standards Body to address any critical post-release vulnerabilities.
Model assessments should include rigorous scientific evaluations of capabilities in cybersecurity, biological threats and other high-risk domains. Specific agentic AI tests could look for attempts to bypass safety guardrails or signs of deception, and ensure best practices, such as digitally watermarking AI-generated images and generating human-readable output tokens to understand model reasoning.
These evaluations would be regularly updated, perhaps quarterly to start, with outdated or saturated benchmarks being deprecated and replaced. Initially, they would be developed in consultation with Frontier Labs, but eventually the Standards Body should build up the technical capacity to create its own held-out tests independent of the Labs to prevent overfitting. Working with the US government, it could promote an ecosystem of third-party auditors to help with the assessments and development of new benchmarks and evaluations...
The framework could apply to Frontier-class models no matter their country of origin or whether they are open or closed "


They are crying to Daddy Trump for help... You will start hearing that leading Chinese models don't meet safety criteria.
 
M

Michael90

Senior Member
Registered Member
9dashline said:
Kimi K3 and GLM 5.3 this week !!

Dario is finna get a heart attack.
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Wait, Zhipu is already ready to release an upgrade so fast after release their current model just a few weeks ago? Seems Zhipu can be considered the best Chinese frontier model , will be interesting to see if Kimi can prove to match/surpass them with their latest model.
 
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