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Not all bot traffic is bad. For years, bots were synonymous with risk: scrapers, scalpers, and credential stuffers trying to steal inventory, stuff stolen credentials into your login page, or scrape pricing and…
OpenAI's math breakthroughs continue, with 700+ papers claiming to solve open problems. Plus: learn how to compare software websites with GPT-6 Astra in ChatGPT Work.
Anthropic on Wednesday launched Claude Haiku 5.5, the first new version of its smallest and most affordable model in nearly The post Anthropic launches Haiku 5.5 at a much lower price appeared first on The New Stack.
Software vendors like to claim unified systems that act as a so-called single pane of glass for any given coding The post OpenSearch veterans launch Infino. Here’s why it matters for agent builders. appeared first on The New Stack.
Technical documentation is increasingly being read by AI agents, creating a new set of demands around how that information is The post What’s up, Docsy? Google’s docs project joins the Linux Foundation as AI agents become readers appeared first on The New Stack.
Every time a UI changes, RPA bots break and on-call engineers wake up. Computer use agents see screens like humans, recover from errors, and follow SOPs without brittle selectors. Here’s what changes for on-call teams.
Stop writing brittle click coordinates. Convert your PyAutoGUI scripts into action objects with the free /v1/parse endpoint. Build a computer use agent that feels like a human.
Legacy RPA gets stuck on Citrix and virtual desktops because brittle selectors break with every update. Computer use agents see and act like a human, so they survive UI changes and keep automating. Book a demo to see how agents handle the work RPA can't.
RPA bots break when screens change, and SOPs only humans can follow. Computer use agents see screens, adapt to updates, and execute validated workflows without rebuilding every time. Learn how agents provide durable automation for regulated environments.
You can run quick one-off tasks with the stateless /v1/predict endpoint at $0.04 per step. For long workflows that need memory, you get stateful sessions with /v1/sessions at $0.10 per session and $0.04 per predict call.
RPA bots break when UIs change, and manual SOPs stay stuck in the past. Computer use agents see the screen, adapt, and follow plain language instructions, no brittle selectors, no rebuilds every release.
Real datasets miss the rare stuff that breaks your model. Synthetic data fills the gaps, lets you test safely, and cuts labeling cost. Here is how.
46% of employees waste time on inefficient file processes every day. That's not just annoying. It's $10 trillion in lost productivity globally. Here's how to stop it.
Traditional RPA creates a maintenance treadmill that drains budget and slows innovation. Computer use agents see the screen and act like humans, so they survive UI changes, follow SOPs directly, and handle exceptions instead of halting. Here is how to move without the risk.
Traditional bots rely on fragile selectors and halt at the first UI change. Computer use agents see the screen, adapt, and stay compliant. Here’s how to move without the risk.
RPA bots break every time the UI changes. Computer use agents read your SOPs and adapt to whatever shows up on screen. Here is the practical path from brittle automation to durable AI agents.
Maintaining brittle bots is expensive. Computer use agents see the screen, adapt to UI changes, and follow SOPs without custom flows. Here is how to move from low-code RPA to durable automation.
RPA vendors are selling you 2020 thinking. AI computer use agents are actually getting things done. Here's the brutal truth about why Automation Anywhere can't keep up.
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