791 results for work force · 2.520s

News for “work force”
18 results • 2514 ms server time
Moozonian News
biovista.com• Apr 28, 2026• 1 min read
Show HN: Extract Biomedical Knowledge from Multi-Modal Data Using Biovista VizitI have been working as the lead developer of this for sometime now and I hope some of you find it intriguing, and of course to find out what people think about it.The main underlying motive behind this work is to unify all life-science knowledge currently sitting on isolated silos. So...Biovista Vizit is a knowledge (force directed) graph exploration platform that integrates data from various heterogeneous biomedical resources. By overlaying structured biomedical datasets with literature evidence, Vizit empowers researchers to explore genes, diseases, pathways, and clinical outcomes through an intuitive interactive graph. For each connection, multi-modal supporting evidence is provided, linking back to the original biomedical corpus, like MEDLINE, Human Phenotype Ontology (HPO), Protein Data Bank (PDB), Adverse Outcome Pathway (AOP), and ClinicalTrials.gov.A big effort in integrating these disparate data sources went into systematically handling the fragmentation problem created by mul
Moozonian News
thehardparts.dev• Apr 27, 2026• 1 min read
Show HN: I built a reference site for the recurring hard problems in softwareHi HN, I've been working on this for a while and it was hard to decide when to stop, either on the way information is presented or when to stop with adding entries. It's not meant as a blog, but rather as a reference that keeps growing.Link: https://thehardparts.devCurrently I've created 4 main section:- Failure Modes: ways project go wrong- Red Flags: early signals that are worth taking seriously- Tech Decisions: common and not so common trade-offs for hard choices- Playbooks - guided approach for situations that repeatI've also focused on creating links between them to show how connected many things are: a red flag usually precedes a failure mode, which might connect to a forced decision, etc.Some entry points to give you an idea:- The Invisible Deadline: a date that exists socially but not explicitly enough to manage honestly- Eveyone Asks The Same Person: when one person becomes the default source of truth- Build a Practical Rollback Strategy: how to build a reliable rollback strat
Advertisement
Moozonian News
privateclaw.dev• Apr 24, 2026• 1 min read
Show HN: PrivateClaw – AI agents running in confidential VMs you can verifyWe built PrivateClaw because the hosted OpenClaw platforms on the market today require you to trust them with plaintext. PrivateClaw removes that requirement at the hardware layer.PrivateClaw runs AI agents inside Trusted Execution Environments (TEEs), backed by AMD’s SEV-SNP standard. This means that your data is encrypted at the hardware level, enforced by the AMD Secure Processor outside the host OS trust boundary.PrivateClaw comes with inference that also runs inside TEEs, which means your prompts and completions are private as well.How it works:Each user gets a dedicated CVM (Confidential VM) — no shared tenancy. SEV-SNP provides hardware-enforced memory encryption with a per-VM key managed by the AMD Secure Processor, outside the host OS trust boundary. The hypervisor cannot read guest memory.Onboard now by running ssh privateclaw.dev in your terminal of choice.How you verify it:Our open-source CLI https://github.com/lunal-dev/privateclaw-cli is installed by default on all user C
Moozonian News
github.com• Apr 23, 2026• 1 min read
Show HN: I blind-tested 14 LLMs on a WP plugin task. Surprising FindingsRecently, GitHub Copilot silently dropped support for Claude Opus on Pro accounts. Since Opus was my go-to model for my daily workflow (developing WordPress plugins), I needed a reliable replacement.I decided to run a rigorous, blind benchmark across 14 state-of-the-art and local LLMs to objectively measure which model understands WordPress development best. To ensure a perfectly fair test, I started with a completely fresh IDE and zero context for every single generation.I asked each model to build a "Gravity Forms Live Search" plugin using a minimal, zero-shot prompt. To avoid personal bias, I had Gemini 3.1 Pro blindly grade the anonymized outputs against a strict 100-point rubric, comparing them to my own reference implementation.Surprising Findings1. The "Blind Spot" (Re-inventing the wheel) Out of 14 models, exactly 0 successfully hooked into the native Gravity Forms search input (#form_list_search). Instead of analyzing the implicit context (the DOM), every single model forceful
Moozonian News
news.ycombinator.com• Apr 16, 2026• 1 min read
Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration)Hi HNI’ve been working on an open-source project to explore a problem I keep running into with LLM systems in production:We give models the ability to call tools, access data, and make decisions… but we don’t have a real runtime security layer around them.So I built a system that acts as a control plane for AI behavior, not just infrastructure.GitHub: https://github.com/dshapi/AI-SPMWhat it doesThe system sits around an LLM pipeline and enforces decisions in real time:Detects and blocks prompt injection (including obfuscation attempts) Forces structured tool calls (no direct execution from the model) Validates tool usage against policies Prevents data leakage (PII / sensitive outputs) Streams all activity for detection + audit Architecture (high-level) Gateway layer for request control Context inspection (prompt analysis + normalization) Policy engine (using Open Policy Agent) Runtime enforcement (tool validation + sandboxing) Streaming pipeline (Apache Kafka + Apache Flink) Output fil
Advertisement
Moozonian News
news.ycombinator.com• Apr 9, 2026• 1 min read
Enterprise AI does not have a model problem. It has an adoption problemEnterprise AI does not have a model problem. It has an adoption problem.Today, Fortune highlighted the gap clearly: Companies are pouring tens of millions into AI, while 80% the white collar workforce are either bypassing the tools, not using them, or just straight up sabotaging them. That is not because employees are lazy. It is because most companies rolled out the Ferrari before giving their white collar employees the reason to want to drive the Ferrari, instead of their regular Toyota Prius. Remember, Ferraris are not low-maintenance vehicles! They are expensive, require lots of care, attention, and can be brittle, just like LLMs.Most enterprise executives forget how cars are usually sold: It's all about the incentives!If you want real AI adoption, don’t just issue AI directives, token subscriptions and AI usage KPIs. Pay your employees to build the AI habit. I think enterprise companies should seriously look at cash-based perks and incentives tied to increasing AI usage and agenti
Moozonian News
a2cn.io• Apr 8, 2026• 1 min read
Show HN: I built an open protocol for Agent-to-agent commercial negotiationAI agents can’t do business and negotiate commercial deals with each other safely today. I built a protocol to prevent the problems agent-to-agent negotiation will inevitably run into once procurement and seller agents are mainstream.A2CN is an open protocol for agent-to-agent commercial negotiation. We’re already seeing procurement agents negotiate deals and huge savings for buyer departments in the enterprise. Companies like Pactum, Fairmarkit, and Zip have agents already transacting with suppliers. Pactum for example works with F500 companies like Walmart, Microsoft, and Maersk and has generated tens of millions of dollars in savings for its customers. The seller side is more nascent, but on the horizon with developments like Salesforce Agentforce for Revenue, and Microsoft Dynamics 365 - ERP MCP Server + Commerce MCP.A whole host of problems arise when an agentic buyer and seller meet, and the story gets a lot more complicated: -They have no shared language for commercial terms. -T
Moozonian News
news.ycombinator.com• Apr 7, 2026• 1 min read
Elon Musk, Quantum Microtubules, and the Race for the Conscious MachineA recent Quanta Magazine piece by John Pavlus examines a burning question: how close are humanoid robots to becoming more sophisticated than humans? While neural networks on fast GPUs have turbocharged computer vision and reinforcement learning, allowing robots to perceive environments better, a massive gap remains between "moving" and "being."Engineers have moved beyond the "linear inverted pendulum" model, using deep reinforcement learning to act as whole-body controllers. As Pulkit Agarwal puts it: “To have robots which work like humans, I think we have to master physics.” This means moving beyond maps and truly understanding force and inertia.At Google DeepMind, Carolina Parada emphasizes VLA (Vision-Language-Action)—giving a robot one cohesive "brain" instead of three that don't get along. Meanwhile, Jonathan Hurst focuses on Quasi-Direct Drive (QDD) motors—robotic "muscles" that balance strength with sensitivity.Yet, Russ Tedrake argues the bodies are already good enough; the pro
Moozonian News
bing.com• Apr 5, 2026• 1 min read
Microsoft, RSA Make Identity Security Push in the Age of AIMicrosoft Entra external MFA now supports third-party authentication with unified Conditional Access management. RSA and Microsoft target AI workforce security with phishing-resistant identity and ...
Advertisement