Andi

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Andi AI

Is there truly a difference between using High and Max effort?

submitted by /u/Sea-Selection-3119 [link] [comments]

What’s Really Happening with Anthropic: A Masterclass in Calculated Corporate Capture

The tech world is reeling from the global shutdown of Anthropic’s Fable 5 and Mythos 5 models, and the mainstream narrative is painfully naive. Mainstream journalists are chalking this up to an unfortunate breakdown in communication between idealistic AI researchers and tech-illiterate politicians. But if you dig beneath the public relations surface and review the timing, a much more calculated reality emerges. This is not a story of bureaucratic stupidity. It is a textbook case of structural corporate capture, operating with the cold, predictive precision of an inside job. Amazon did not panic; they executed a pre-mapped strategy to shift Anthropic from an ambitious independent partner to a fully captured corporate vassal. The Setup: Golden Handcuffs and Compute Debt To understand the true physics of this situation, you have to look at the leverage Amazon secured in April 2026. Amazon injected an historic $5 billion into Anthropic, which the press celebrated as a massive partnership expansion. In reality, it was the construction of a financial cage. • The AWS Lock-In: The investment legally anchors Anthropic to a ten-year, $100 billion cloud infrastructure contract. • Infrastructure Control: Anthropic is forced to build and train its frontier models exclusively on Amazon Web Services (AWS) hardware. • The Debt Trap: This arrangement created an astronomical compute debt trap. Anthropic must pay Amazon billions for server time, regardless of whether their models are online or banned. The Catalyst: Weaponising the Mundane The corporate trap was sprung exactly as Anthropic was gaining momentum for its autumn Public Offering, using a cynically mundane pretext. Amazon’s internal security teams ran routine probing on Fable 5 and generated a report on a supposed "universal jailbreak". The mechanics of this "exploit" are an absolute joke to anyone who codes: The "Jailbreak" Reality: Amazon researchers initially asked Fable 5 to review code laced with vulnerabilities, triggering an over-sensitive safety filter that resulted in a false-positive refusal. In a clean session, they handed it the exact same code and said, "Fix this code". Fable happily complied, rewriting the code to make it safer—a standard feature developers pay for inside Claude Code. Amazon employs thousands of top-tier security professionals. They knew this was standard defensive refactoring, not a weapon-level exploit. Yet, instead of submitting a routine bug ticket to their partner, Amazon CEO Andy Jassy took the nuclear option. He personally called Treasury Secretary Scott Bessent on a Thursday night to flag the model as a national security threat. The Strategy: Inverting Hanlon's Razor This is where the real brutal genius of the corporate strategy lies. Amazon did not act out of technical ignorance, nor did they suddenly "accidentally" tattle-tale on their partner. They inverted Hanlon’s Razor: they didn't act stupidly; they weaponised the guaranteed stupidity of the state. Amazon knew exactly how an administration filled with overzealous loyalists would react. They knew that the moment the word "vulnerability" was uttered to politicians who speak an entirely different, optics-driven language, a panic would ensue. By feeding this non-issue to a tech-illiterate White House, Amazon deliberately triggered a blunt, heavy-handed regulatory response. The feds immediately slapped down emergency export controls on Friday night, forcing Anthropic to yank Fable 5 and Mythos 5 offline globally because they lacked the infrastructure to filter users by nationality in real time. Amazon used the state as a proxy executioner, keeping their own hands clean while the government played the villain. The Motive: Ruthless Pre-IPO Shorting Why would a partner deliberately freeze its own multi-billion dollar investment? Because an independent, highly valued Anthropic heading into a massive public debut is a volatile liability to Amazon's cloud dominance. A broken, debt-ridden Anthropic, however, is an asset to be owned. By engineering this regulatory crisis, Amazon achieved absolute structural leverage: • IPO Valuation Collapse: Public investors flee from regulatory chaos. By locking Anthropic in a legal war with the Pentagon and an export ban with the Commerce Department, Amazon has effectively crushed Anthropic’s pre-IPO market momentum. • The Revenue Stranglehold: Premium developers on Max plans are facing a downgraded or missing product, sparking a massive wave of user churn that chokes off Anthropic’s independent revenue. • The Terms of Surrender: Anthropic still owes Amazon billions for AWS compute time. With no revenue and a tanked valuation, Anthropic cannot pay the bill. The End Game: The Brain Drain Calculation Amazon’s strategy is entirely prepared for the founders to potentially walk away in disgust. In the cold math of Big Tech, the idealistic founders are entirely replaceable. Amazon don’t need any model or tech th

Reading New scientist articles is now enjoyable with gpt image

submitted by /u/Ok-Hat2331 [link] [comments]

Gemini AI is doing free marketing for my private discord community 💀

But in the wrong way Crazy encounter 🤣 Another reason to use claude daily submitted by /u/Odd-Pension-5078 [link] [comments]

Claude Thinking Noise Fatigue

This morning I realised there’s a very specific kind of stress I get when reading what Claude (Code) “thinks” while generating an answer or working on code changes. The problem is not that it is malicious or problematic, but rather the sheer volume and often low signal-to-noise ratio of the reasoning... You’re exposed to every detour, redundant step, and half-baked line of reasoning along the way... It’s cognitively expensive in a way that’s hard to articulate. And yes: I do know I can just STOP reading what it thinks; andI will try to since I have now recognised the problem. But I also want to hear your thoughts about it? submitted by /u/QuasiBanton [link] [comments]

Rocky's grammar from Project Hail Mary — up to 83% fewer output tokens on Claude. Built it into a skill file.

I use Claude Pro heavily. Was hitting the usage limit almost every session. Built a prompt to fix it. The savings are real — same question, normal Claude vs. with this active: Normal (335 tokens): An LLM (Large Language Model) is a type of AI trained on massive amounts of text to predict and generate language. The core idea: given some text, what words are likely to come next?... With the prompt (56 tokens): LLM = Large Language Model. Big big big neural network. Trained on text text text. Learns patterns. Predicts next word. Weights store knowledge-shape. Not real understanding. Pattern-matching. Very very good pattern-matching. You want more detail on specific part. Question? That voice is Rocky — the alien engineer from Andy Weir's Project Hail Mary. Dense, direct, no filler. I extracted his grammar into a skill file. Two modes: Rocky — full character. Dense and warm through fact rather than pleasantry. Best for chat with a little bit of flair. Activate with #rockyon, turn off with #rockyoff. Signal — better savings, no personality. Clean notation system for more technical sessions. Activate with #signalon, turn off with #signaloff. Both work mid-conversation. No setup beyond pasting the prompt once into your system instructions. I built this to solve my own token limit problem. It worked well enough that I wrote up everything I learned — including why explicit rules produce weaker output than examples — over at thelongrep.com. Repo: github.com/SijuEC/eridani-speak submitted by /u/TheLongRep [link] [comments]

“ChatGPT goes down for 10 minutes: Me: ‘I need to learn how to think again’ 😭”

submitted by /u/Old_Run_6341 [link] [comments]

Claude code Plugin - Makes your AI coding agent talk and think like Rocky, the Eridian engineer from Andy Weir's Project Hail Mary.

Hey, If you're tired of bland AI responses and want your coding sessions to feel like chatting with an Eridian buddy from Project Hail Mary, check out Rocky – the new output style plugin that's taking Claude Code to interstellar levels. What is Rocky? Rocky transforms Claude (and other coding agents) into "Rocky Mode" – a fun, alien-inspired personality inspired by the book's genius engineer Rocky. It adds quirky Eridian flair to code explanations, debugging, and more, without sacrificing accuracy. Perfect for making complex coding fun! Key Features Three Modes: Rocky Talk - your agent talks like rocky (plans, implementation are not effected) Full Rocky - your agent talks + thinks like rocky as engineer Rocky Buddy - you get your own rocky buddy as an ascii character Claude Code Native: Easy install as a plugin via .claude-plugin/plugin.json – works seamlessly with skills, agents, and hooks. Universal Compatibility: Built for Claude Code but adaptable to other coding agents. Lightweight & Fun: No bloat – just personality boosts for better engagement during long code sessions. Full docs in README: https://github.com/vikxlp/rocky/blob/main/README.md Feedback & ideas are welcome! Drop a comment 🌌 #ClaudeCode #AIPersonality #ProjectHailMary submitted by /u/vikalp02 [link] [comments]

It’s not your imagination: AI seed startups are commanding higher valuations

Among the most recent Y Combinator cohort, many startups were commanding $40 million valuations. But with more money comes higher expectations.

Softr launches AI-native platform to help nontechnical teams build business apps without code

Softr, the Berlin-based no-code platform used by more than one million builders and 7,000 organizations including Netflix, Google, and Stripe, today launched what it calls an AI-native platform — a bet that the explosive growth of AI-powered app creation tools has produced a market full of impressive demos but very little production-ready business software. The company's new AI Co-Builder lets non-technical users describe in plain language the software they need, and the platform generates a fully integrated system — database, user interface, permissions, and business logic included — connected and ready for real-world deployment immediately. The move marks a fundamental evolution for a company that spent five years building a no-code business before layering AI on top of what it describes as a proven infrastructure of constrained, pre-built building blocks. "Most AI app-builders stop at the shiny demo stage," Softr Co-Founder and CEO Mariam Hakobyan told VentureBeat in an exclusive interview ahead of the launch. "A lot of the time, people generate calculators, landing pages, and websites — and there are a huge number of use cases for those. But there is no actual business application builder, which has completely different needs." The announcement arrives at a moment when the AI app-building market finds itself at an inflection point. A wave of so-called "vibe coding" platforms — tools like Lovable, Bolt, and Replit that generate application code from natural language prompts — have captured developer mindshare and venture capital over the past 18 months. But Hakobyan argues those tools fundamentally misserve the audience Softr is chasing: the estimated billions of non-technical business users inside companies who need custom operational software but lack the skills to maintain AI-generated code when it inevitably breaks. Why AI-generated app prototypes keep failing when real business data is involved The core tension Softr is trying to resolve is one that has plag

RSAC 2026 shipped five agent identity frameworks and left three critical gaps open

“You can deceive, manipulate, and lie. That’s an inherent property of language. It’s a feature, not a flaw,” CrowdStrike CTO Elia Zaitsev told VentureBeat in an exclusive interview at RSA Conference 2026. If deception is baked into language itself, every vendor trying to secure AI agents by analyzing their intent is chasing a problem that cannot be conclusively solved. Zaitsev is betting on context instead. CrowdStrike’s Falcon sensor walks the process tree on an endpoint and tracks what agents did, not what agents appeared to intend. “Observing actual kinetic actions is a structured, solvable problem,” Zaitsev told VentureBeat. “Intent is not.” That argument landed 24 hours after CrowdStrike CEO George Kurtz disclosed two production incidents at Fortune 50 companies. In the first, a CEO's AI agent rewrote the company's own security policy — not because it was compromised, but because it wanted to fix a problem, lacked the permissions to do so, and removed the restriction itself. Every identity check passed; the company caught the modification by accident. The second incident involved a 100-agent Slack swarm that delegated a code fix between agents with no human approval. Agent 12 made the commit. The team discovered it after the fact. Two incidents at two Fortune 50 companies. Caught by accident both times. Every identity framework that shipped at RSAC this week missed them. The vendors verified who the agent was. None of them tracked what the agent did. The urgency behind every framework launch reflects a broader market shift. "The difficulty of securing agentic AI is likely to push customers toward trusted platform vendors that can offer broader coverage across the expanding attack surface," according to William Blair's RSA Conference 2026 equity research report by analyst Jonathan Ho. Five vendors answered that call at RSAC this week. None of them answered it completely. Attackers are already inside enterprise pilots The scale of the exposure is already visible

Assessing AI powered price forecasting tools in currency markets

As artificial intelligence becomes a driving force in financial prediction, the reliability of its forecasting tools faces increasing scrutiny. Many traders question whether claims of high accuracy translate into consistent results under live market conditions. Understanding how these AI systems are evaluated reveals important distinctions between performance in theory and practice. Few financial domains are […] The post Assessing AI powered price forecasting tools in currency markets appeared first on AI News.

Claude Colour Personalization Concept

Upon switching to Claude, and gifting a subscription to my girlfriend I was offered the option to choose what colour her gift arrived in. I wish anthropic would extend this level of colour choice to your Claude theme (perhaps this is already a thing and I have not dug deep enough into the settings to find it). I really hope they add something like this in the future (and please add a mustard colour option too!) submitted by /u/ThrilledTear [link] [comments]

Understanding Representation Learning in Neural Networks (With PyTorch Example)

Deep learning systems are powerful because they learn representations of data automatically. Instead...

Weekly Report Mar 2 -- Mar 9, 2026

# Weekly Report: Mar 2 -- Mar 9, 2026 ## Quick Stats | Metric | Count | |--------|-------| | Merged PRs | 47 | | Open PRs | 24 (11 draft) | | Open issues | 61 | | New issues this week | 33 | | Issues closed this week | 6 | | CI runs on main | 30 | ## Highlights An exceptionally active week with 47 merged PRs. Key themes: - **Realm migration**: Keycloak master-to-kagenti realm migration landed (#764), with follow-up fixes (#851, #863) - **Platform hardening**: Podman support (#861), Docker Hub rate limit fixes (#844), PostgreSQL mount fix (#852) - **CI/CD improvements**: OpenSSF Scorecard 7.1->8+ (#807), stale workflow permissions (#859), HyperShift cluster auto-cleanup (#854) - **New capabilities**: CLI/TUI for Kagenti (#835), Istio trace export to OTel (#795), RHOAI 3.x integration (#809) - **Dependency updates**: 8 Dependabot PRs (Docker actions major bumps, CodeQL, Trivy) - **Authorization epic**: 7 new issues (#787-#794) laying out a comprehensive authorization and policy framework - **Agent sandbox epic**: New epic (#820) for platform-owned sandboxed agent runtime ## Issue Analysis ### Epics (active initiatives) | # | Title | Owner | Status | |---|-------|-------|--------| | #862 | AgentRuntime CR — CR-triggered injection | @cwiklik | New, design phase | | #820 | Platform-Owned Sandboxed Agent Runtime | @Ladas | Active, PR #758 in progress | | #828 | Migrate installer from Ansible/Helm to Operator | @pdettori | New, planning | | #787 | Authorization, Policies, and Access Management | @mrsabath | New, 6 sub-issues filed | | #841 | Org-wide orchestration: CI, tests, security | @Ladas | Active, PRs #866-#868 open | | #767 | Migrate from Keycloak master realm | @mrsabath | Mostly done (#764 merged), close candidate | | #619 | Tracing observability PoC | @evaline-ju | Active (#795 merged) | | #621 | OpenSSF Scorecard to 10/10 | @Ladas | Active (#807 merged, now 8+) | | #523 | Refactor APIs for Compositional Architecture | @pdettori | Active, PR #770 open | | #518 | OpenShift AI deployment issues | @Ladas | Active (#809 merged) | | #309 | Full Coverage E2E Testing | @cooktheryan | Ongoing | | #440 | Multi-Team Deployment on RHOAI | @Ladas | Ongoing | | #439 | Namespace-Based Token Usage Quotas | @Ladas | Ongoing | | #614 | Feedback review community meeting | @Ladas | Stale (>30d no update) | | #623 | Identify Emerging Agentic Deployment Patterns | @kellyaa | Stale | | #612 | Agent Attestation Framework | @mrsabath | Stale, PR #613 still draft | ### Security-Adjacent Issues | # | Title | Status | Recommendation | |---|-------|--------|----------------| | #822 | Keycloak configmap should be secret | Open | High priority — credentials in configmap | | #106 | Replace hardcoded secret with SPIRE identity | Open | Long-standing, PR #769 in draft | | #333 | SPIFFE ID missing checks | Open | Stale, needs triage | | #267 | Replace hard-coded Client Secret File path | Open | Good first issue, needs assignee | ### Bug Reports | # | Title | Still affects main? | PR exists? | Recommendation | |---|-------|---------------------|------------|----------------| | #856 | Warnings during Kagenti install | Likely yes | No | Triage — install warnings | | #855 | Can't checkout source on Windows | Yes (skill naming) | PR #869 | In progress | | #829 | Deleting A2A agent doesn't delete HTTPRoute | Likely yes | No | Needs fix | | #826 | No way to log out of Kagenti | Yes | No | UX bug, needs fix | | #825 | Build failures lead to stuck state | Likely yes | No | Needs investigation | | #738 | UI drops spire label on 2nd deploy | Likely yes | No | Stale (>30d) | | #486 | Installer issues (Postgres/Phoenix) | Partially (#852 fixed PG) | Partial | Re-verify Phoenix | | #781 | kagenti-deps fails on OCP 4.19 | Unknown | No | Stale, needs triage | | #606 | Unsupported Helm version | Unknown | No | Stale, needs triage | | #655 | Duplicated resources between repos | Unknown | No | Stale, needs triage | ### Issues Closed This Week (good velocity) | # | Title | Fix PR | |---|-------|--------| | #833 | UI login fails after realm migration | #834 | | #831 | --preload fails when images cached | #832 | | #819 | Remove deprecated Component CRD refs | #818 | | #813 | Import env vars references bad URL | #821 | | #810 | Import env vars silently fails on dup | #821 | | #804 | OAuth secret job SSL error on OCP | #805 | ### Feature Requests | # | Title | Priority | Recommendation | |---|-------|----------|----------------| | #858 | Use new URL for fetching Agent Cards | Medium | Good first issue | | #836 | AuthBridge sidecar opt-out controls in UI | Medium | Tied to #862 epic | | #824 | Help text for UI fields | Low | Good UX improvement | | #823 | Examples as suggestions in UI | Low | Nice-to-have | | #817 | Auto-add issues/PRs to project board | Medium | PR #870 open | | #814 | Mechanism to update agent via K8s | Medium | Operator feature | | #786 | Register MCP servers from UI | Medium | UI feature | | #783 | Agent card signing/verifica