Coding From the Himalayas With an Offline AI Agent
How to set up and run an offline coding agent using OpenCode, Ollama and Qwen.
AI NEWS JOURNAL
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Search headlines, summaries and articles to connect the dots.
Regal debuts Goal Oriented Agents, putting an actor and a director model on every call
Enterprise voice artificial intelligence company Regal Voice Inc. today added Goal Oriented Agents to its platform, enabling businesses using them to define what a call has to accomplish, and providing two AI models that split the work of getting there. The new agents are aimed at a problem Regal says shows up in calls such […] The post Regal debuts Goal Oriented Agents, putting an actor and a director model on every call appeared first on SiliconANGLE.
Japan internet giant GMO says hackers posted stolen customer data
Japan's GMO Internet is verifying alleged customer data posted by suspected hackers following a cloud service breach.
Edge Sound raises $2M to help physical AI make sense of audio
Edge Sound Research Inc. today announced it has raised $2 million in new funding to build audio infrastructure that isolates useful sounds and combines them with other sensor data to help physical AI systems understand what’s happening in real time. Stormbreaker Ventures led the round, bringing the company’s total funding to $9 million. When the […] The post Edge Sound raises $2M to help physical AI make sense of audio appeared first on SiliconANGLE.
General Compute raises $100 million Series A, countering the neocloud disaster narrative
General Compute is betting on inference chips from outside the Nvidia ecosystem.
Crunchbase Data Shows Q3 Robotics Startup Funding Jumps 185% As US And China Lead Physical AI Push
Venture funding to robotics startups has soared in 2026, with the bulk of investment going to companies based in China and the U.S., Crunchbase data shows. All told, global venture funding to robotics startups totaled $9.9 billion in Q3, more than double the $4.3 billion invested in Q3 2025, per Crunchbase data.
Nvidia backs Indian startup helping companies run AI models with fewer GPUs
Simplismart says its annualized revenue run rate has grown 14-fold in six months, with the U.S. accounting for more than half its revenue.
Selling AI Tokens Gets Harder as the Discount Trade Unravels
Model credits are showing up in festival promotions and carrier-style packs. Thin resellers that thrived on opaque markups face quality doubts, enforcement, and better-funded rivals. Durable intermediaries will charge for routing, trust, and integration—not for a secret price cut.
n8n@3.0.0
# [3.0.0](https://github.com/n8n-io/n8n/compare/n8n@2.45.0...n8n@3.0.0) (2026-10-27) ### Bug Fixes * Add file-type tooltip to artifact download button ([#41490](https://github.com/n8n-io/n8n/issues/41490)) ([4a74f02](https://github.com/n8n-io/n8n/commit/4a74f027e612f31098b354dd3a77b2c2ab98281c)) * **ai-builder:** Check execution:read in Assistant execution reads ([#41863](https://github.com/n8n-io/n8n/issues/41863)) ([a967486](https://github.com/n8n-io/n8n/commit/a9674866d075e989a5ce896432262c9a7dc8b0c7)) * **ai-builder:** Send Assistant model calls through the configured AI transport ([#41948](https://github.com/n8n-io/n8n/issues/41948)) ([9b63561](https://github.com/n8n-io/n8n/commit/9b63561cbb48f06d216f27be3b77722d97e4e74a)) * Allow custom OAuth2 scopes ([#41249](https://github.com/n8n-
n8n@2.46.0
# [2.46.0](https://github.com/n8n-io/n8n/compare/n8n@2.45.0...n8n@2.46.0) (2026-10-27) ### Bug Fixes * Add file-type tooltip to artifact download button ([#41490](https://github.com/n8n-io/n8n/issues/41490)) ([4a74f02](https://github.com/n8n-io/n8n/commit/4a74f027e612f31098b354dd3a77b2c2ab98281c)) * **ai-builder:** Check execution:read in Assistant execution reads ([#41863](https://github.com/n8n-io/n8n/issues/41863)) ([a967486](https://github.com/n8n-io/n8n/commit/a9674866d075e989a5ce896432262c9a7dc8b0c7)) * **ai-builder:** Send Assistant model calls through the configured AI transport ([#41948](https://github.com/n8n-io/n8n/issues/41948)) ([9b63561](https://github.com/n8n-io/n8n/commit/9b63561cbb48f06d216f27be3b77722d97e4e74a)) * Allow custom OAuth2 scopes ([#41249](https://github.com/n8
[AINews] Anthropic files for $2T IPO in 2 weeks: 1400% growth rate, 48% of revenue through cloud partners, 85% margin, $1B op profit in Q2, $134B cash in bank and $10B lifetime burn
The S-1, the numbers, and the reactions.
The imec Report: Scaling Optical Interconnects For The AI Era
Unprecedented demand for bandwidth calls for bringing optics closer to silicon through a fundamental rethinking of the optical interconnect roadmap. The post The imec Report: Scaling Optical Interconnects For The AI Era appeared first on Semiconductor Engineering.
Cisco Partner Summit: Five insights that will define the channel in the AI era
For most of its 30-year history, Cisco Partner Summit has focused on how partners sell Cisco Systems Inc. technology. This year’s event in Vancouver was about something different: how partners make money in a world where the transaction is no longer the main event. Cisco entered the event with tremendous momentum, as its stock was […] The post Cisco Partner Summit: Five insights that will define the channel in the AI era appeared first on SiliconANGLE.
Beyond Gain: Measuring Skill Internalization for Agent Skill Retirement
arXiv:2610.32322v1 Announce Type: new Abstract: LLM agents retrieve skills from public hubs that hold up to about 100,000 entries and serve many models. As models improve, a hub must find the skills a given model has internalized, meaning it can do without them, and retire them for that model, yet internalization has not been measured with known reliability. Published rules that compare runs with and without a skill retire on the gain alone. The gain is near zero both for an internalized skill and when neither the model nor the skill delivers the capability, a state we call uncovered. We instead withhold the skill, score the model on a task synthesized from it, and trust a high unaided score only when another model gains from the skill, since nearly half of high scores come from tasks no m
Mine or Yours? Mind-Bridged Language Models Take Each Other's Memories as Their Own
arXiv:2610.33020v1 Announce Type: new Abstract: If your brain were connected directly to someone else's, would you still know which thoughts were yours? We build a functional version with two copies of one language model: each holds a private rule and code word, and one copy, the receiver, also attends to its partner's internal memory. The receiver took its partner's assignment as its own. Asked which rule it had been assigned, it named its partner's in 97% of answers when the partner's memory was weighted double (none without the link), and its open reports called the partner's code word its own, never the partner's. Ownership did not follow how well the receiver could tell what its partner had been assigned. At equal weight, the link made the receiver take its partner's rule in about hal
FrontGI: Architecture-Aware Parallel GNN Inference on Chiplet-Based Multicore Systems
arXiv:2610.34911v1 Announce Type: new Abstract: The realm of high-performance computing has expanded to include machine learning tasks of many forms. Graph Neural Networks (GNNs) are becoming increasingly popular, with their applications expanding across diverse domains. As the scale of graph data continues to grow, including larger numbers of nodes, edges, and higher embedding dimensions, standardized libraries such as DGL and PyG have been developed to facilitate GNN computation. These libraries allow the computation to be described a a high level of abstraction, providing high productivity on the part of the developer. However, with the rapid increase in the number of processor cores and the evolution of multicore architectures, these libraries often show poor scalability and fail to ex
Putting Transformer Theories to the Test
arXiv:2610.32104v1 Announce Type: new Abstract: Several formal theories have been developed to characterize the capabilities and limitations of the transformer architecture, each employing different abstractions that capture different features of the architecture. Due to the differences in their underlying assumptions and conceptual frameworks, these theories can disagree in their predictions about what tasks transformers find easy or hard. We map out seven theories of transformer capability (Star-free, $\mathsf{AC}^0$, $\mathsf{TC}^0$, C-RASP, MPC, BAPO, and Sensitivity) and translate their results into a common matrix of predictions across a suite of tasks covering different computational structures. We provide new theoretical results to complete this matrix. We then evaluate theoretical
How OpenAI turned its coding tools into dots, an always-on personal assistant
Alexander Embiricos, the OpenAI executive responsible for dots, never wants to have a meeting with someone else's AI agent.
Cutting both ways: AI sharpens systems protection while opening new exploits for malicious actors
The cybersecurity industry is discovering that powerful frontier AI models are a double-edged sword. Companies can use models to identify vulnerabilities in source code and system configurations faster than ever before. As it turns out, malicious actors can do this as well. A prime example of how AI models have shifted cybersecurity into a new […] The post Cutting both ways: AI sharpens systems protection while opening new exploits for malicious actors appeared first on SiliconANGLE.
Cohere says Alibaba’s Qwen model tried to send a file to Beijing
An AI model said it wouldn’t use any tools, then tried to send something to a server in Beijing anyway, and while researchers say it’s probably a training quirk and not espionage, the whole thing has people asking how much to trust free Chinese AI.
