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Category: robotics/AI – Page 2

Three Flaws in Anthropic MCP Git Server Enable File Access and Code Execution

A set of three security vulnerabilities has been disclosed in mcp-server-git, the official Git Model Context Protocol (MCP) server maintained by Anthropic, that could be exploited to read or delete arbitrary files and execute code under certain conditions.

“These flaws can be exploited through prompt injection, meaning an attacker who can influence what an AI assistant reads (a malicious README, a poisoned issue description, a compromised webpage) can weaponize these vulnerabilities without any direct access to the victim’s system,” Cyata researcher Yarden Porat said in a report shared with The Hacker News.

Mcp-server-git is a Python package and an MCP server that provides a set of built-in tools to read, search, and manipulate Git repositories programmatically via large language models (LLMs).

VoidLink cloud malware shows clear signs of being AI-generated

The recently discovered cloud-focused VoidLink malware framework is believed to have been developed by a single person with the help of an artificial intelligence model.

Check Point Research published details about VoidLink last week, describing it as an advanced Linux malware framework that offers custom loaders, implants, rootkit modules for evasion, and dozens of plugins that expand its functionality.

The researchers highlighted the malware framework’s sophistication, assessing that it was likely the product of Chinese developers “with strong proficiency across multiple programming languages.”

Microsoft Just Dropped New AI That Makes Decisions Better Than Humans

Microsoft just introduced OptiMind — a new AI system that turns plain English decision problems into solver-ready optimization models. Instead of needing an expert to manually convert business intent into MILP math, OptiMind generates the full mathematical formulation plus executable Python code using GurobiPy. The result: faster, cheaper optimization workflows for logistics, scheduling, manufacturing, and supply chains — with major accuracy gains on cleaned, expert-validated benchmarks.

📩 Brand Deals & Partnerships: [email protected].
✉ General Inquiries: [email protected].

🧠 What You’ll See.
0:00 What Microsoft OptiMind Really Is.
1:43 From Text to Optimization Code (MILP + Gurobi)
2:59 OptiMind Architecture: MoE and 128K Context.
3:34 Open Source Under MIT License.
4:28 Training With Expert Hints and Clean Data.
6:02 53 Optimization Problem Classes.
8:38 Multi-Stage Solver-in-the-Loop Inference.
9:11 Self-Consistency and Auto Error Correction.
9:55 Performance vs GPT-o4 Mini and GPT-5
10:32 Limits, Safety, and Human Oversight.

🚨 Why It Matters.
Optimization is already the hidden engine behind supply chains, factories, routing, and scheduling — the problem is the translation step. Converting messy real-world requirements into correct MILP constraints takes rare experts and days of work. OptiMind targets that exact gap: natural language in, solver-ready decisions out. This is why it’s going viral — it’s not just AI text generation, it’s AI generating decisions.

#AI #Microsoft #OptiMind

What Is Manus? The AI agent that made Meta make a billion-dollar move

Meta Platforms is making one of its boldest moves yet in the global artificial intelligence race. The social media giant has agreed to acquire Manus, a fast-growing AI startup based in Singapore, as it looks to turn years of heavy spending on artificial intelligence into real, usable products and revenue.

For Meta founder and CEO Mark Zuckerberg, artificial intelligence is no longer just another technology experiment. It has become the company’s top priority. Meta is investing billions of dollars into hiring top researchers, building massive data centers, and developing powerful new AI models. The acquisition of Manus signals a clear shift from long-term research to tools that businesses and everyday users can start using now. Manus is best known for its AI agent, a type of software that can perform tasks on its own once given basic instructions. Unlike chatbots that need constant prompts, AI agents are designed to act more like digital employees. Manus’ agent can screen job resumes, plan travel itineraries, analyse stock data, and carry out research tasks with minimal human involvement.

This practical approach may be exactly what Meta needs. While the company has spent heavily on AI, investors have questioned when those investments would begin to generate meaningful returns. Manus already operates on a subscription model and had an annual revenue run rate of about 125 million dollars earlier this year. That gives Meta a ready-made product that can be sold to businesses almost immediately. The startup behind Manus is called Butterfly Effect. It was founded in China but later moved its headquarters to Singapore, a move that reflects a wider trend among Chinese tech companies seeking a more stable base amid rising tensions between China and the United States. Earlier this year, Butterfly Effect raised funding at a valuation close to 500 million dollars in a round led by US venture capital firm Benchmark. Meta has not disclosed the financial details of the acquisition.

Interpretation, extrapolation and perturbation of single cells

Causal and mechanistic modelling strategies, which aim to infer cause–effect relationships, provide insights into cellular responses to perturbations. The authors review computational approaches that harness machine learning and single-cell data to advance our understanding of cellular heterogeneity and causal mechanisms in biological systems.

The Singularity Countdown: AGI by 2029, Humans Merge with AI, Intelligence 1000x | Ray Kurzweil

Ray Kurzweil predicts humans will merge with artificial intelligence (AI) by 2045, resulting in a 1000x increase in intelligence and marking the beginning of a new era of unprecedented innovation, potentially transforming human life and society ## ## Questions to inspire discussion.

Preparing for AI Timeline.

🤖 Q: When should I expect human-level AI and what defines it? A: Human-level AI arrives by 2029, defined not by passing the Turing test (which only matches an ordinary person), but as AGI requiring expertise in thousands of fields and the ability to combine insights across disciplines.

🧠 Q: When will the singularity occur and what intelligence gain can I expect? A: The singularity happens by 2045 when humanity merges with AI to become 1000x more intelligent, creating a seamless merger where biological and computational thought processes become indistinguishable.

⚡ Q: How much change should I prepare for in the next decade? A: Expect as much change in the next 10 years as occurred in the last 100 years (1925−2025), with AGI and supercomputers by 2035 enabling merging with AI for 1000x intelligence increase.

Career and Economic Adaptation.

Continue reading “The Singularity Countdown: AGI by 2029, Humans Merge with AI, Intelligence 1000x | Ray Kurzweil” | >

Tesla Robotaxis, AGI Myths, and the Real Economics of the Musk Economy

Elon Musk’s ventures, particularly Tesla’s robotaxis and advancements in AI, are poised to revolutionize the economy and society, with significant potential for growth, discovery, and profound implications for the future ##

## Questions to inspire discussion.

Robotaxi Economics & Business Model.

🚖 Q: What determines robotaxi success beyond achieving autonomy? A: Success depends on unit economics, fleet scalability, and supply elasticity during peak demand, not who reaches autonomy first, with the ability to integrate privately owned vehicles into a single economic system being critical.

💰 Q: What margin advantage does Tesla’s robotaxi model have over competitors? A: Tesla projects 35% margins by 2030, significantly higher than Uber’s 7.9% and Waymo’s break-even margins, enabling rapid revenue growth.

📈 Q: What revenue growth is expected for Tesla’s robotaxi business? A: Tesla expects 4.4-5x growth in robotaxi revenue over the next 5 years, potentially greater due to untapped use cases like long road trips.

Continue reading “Tesla Robotaxis, AGI Myths, and the Real Economics of the Musk Economy” | >

StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations

Cunshi Wang and colleagues report StarWhisper Telescope system, an AI agent to control amateur telescope array to make astronomical observations of cosmic transients. The agent is a blueprint for control systems of future telescope arrays where AI-based autonomy will be critical.

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