After interviewing 12 AI researchers from OpenAI, Anthropic, and Google, this guy noticed they all use the same 10 prompts.
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Alibaba researchers said a model they were training managed to bypass internal firewall protections and started using part of the GPUs for cryptocurrency mining instead of training tasks.
📊 @tech
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Taara, a former Google X project, introduced Taara Beam at MWC 2026 in Barcelona. The device sends internet traffic through a beam of invisible infrared light and reaches speeds up to 25 Gbps over distances up to 10 km.
The unit weighs about 8 kg and mounts on rooftops or poles. Inside is a silicon photonics platform with an optical phased array that contains more than 1,000 tiny emitters. They form and steer the light beam electronically, with no moving parts.
The system carries the same type of optical signal used inside fiber cables, but through open air. The module that controls the beam is about the size of a finger.
The key advantage is deployment time. Fiber rollout can take months. A Beam link can be installed in hours.
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Chinese police are using a new AI patrol robot with a spherical design. Its top speed reaches about 60 km/h.
The robot moves by rolling on a single large wheel-like body. The shape allows it to accelerate quickly while staying stable on the ground.
The form factor is built for speed during patrol and pursuit.
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Researchers at Eon Systems say they built the first full digital emulation of an animal brain that can control a body inside a simulation.
The team copied the brain of a fruit fly and reconstructed its connectome. This is a full map of neurons and the connections between them. The model includes about 140,000 neurons with their synaptic links.
The key step was connecting this brain model to a simulated body. The system runs a full loop: environment → sensors → brain signals → motor commands → movement. The virtual fly shows several basic behavior patterns.
The approach uses a biological brain map instead of training a neural network. Scaling it remains the main challenge. A human brain contains about 86 billion neurons.
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🦞 China hosts OpenClaw install events that draw 1,000 people
Developers held a public event near the Tencent office in Shenzhen where anyone could get OpenClaw installed. Around 1,000 people reportedly showed up. Similar events also took place in Shanghai, Beijing, and other cities.
The program is tied to a broader rollout of OpenClaw infrastructure in China. The plan includes “Lobster service zones”, physical or cloud locations where OpenClaw is already deployed and maintained.
Operators of these zones may receive funding for hosting. Developers who build applications for priority sectors can get subsidies up to 2M yuan. Projects recognized as demonstration cases can receive one-time grants up to 1M yuan.
📊 @tech
Developers held a public event near the Tencent office in Shenzhen where anyone could get OpenClaw installed. Around 1,000 people reportedly showed up. Similar events also took place in Shanghai, Beijing, and other cities.
The program is tied to a broader rollout of OpenClaw infrastructure in China. The plan includes “Lobster service zones”, physical or cloud locations where OpenClaw is already deployed and maintained.
Operators of these zones may receive funding for hosting. Developers who build applications for priority sectors can get subsidies up to 2M yuan. Projects recognized as demonstration cases can receive one-time grants up to 1M yuan.
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Cortical Labs placed about 200,000 human brain cells in a petri dish and connected them to a computer running DOOM.
Game data is converted into electrical signals and sent to the neurons. Their activity is translated back into commands for movement, aiming, and shooting. Through feedback the neural network gradually learns to navigate the 3D environment.
The system uses biological neurons instead of digital neural networks. Human brains consume far less energy than modern AI systems.
Energy limits remain a major constraint for scaling AI.
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Anthropic released a new feature for Claude Code that reviews GitHub pull requests using multiple AI agents. The system analyzes PRs, leaves comments directly in the diff, and posts a summary with the main findings.
Several agents review the same changes in parallel, each focusing on different aspects of the code. Anthropic tested the system internally for several months.
During testing the share of PRs with meaningful review comments rose from 16% to 54%. Fewer than 1% of results were marked incorrect by engineers. In large PRs of about 1,000 lines the tool found at least one issue in 84% of cases, with an average of 7.5 issues per PR.
The estimated cost is about $15–$25 per pull request.
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Google Play began enforcing new rules on March 1 for apps that consume too much battery while running in the background.
The system focuses on wake locks. These keep the CPU active when the screen is off. If an app holds a wake lock for more than 2 hours on average with the screen off in over 5% of sessions during a 28-day period, the app may face penalties.
Google can add warnings on the app’s store page and reduce its visibility in search and recommendations.
Battery usage is now treated as a technical quality signal alongside crashes and freezes.
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