Alibaba launches AI-native enterprise platform - MSN
Alibaba launches AI-native enterprise platform MSN
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60% of Consumers Want Approval Gates for AI Spending. Who Builds Them?
Visa just published a study of 2,000 consumers on AI agents and spending. The finding that should dominate every conversation about agentic commerce: 60% of respondents want human approval gates before an AI agent makes purchases on their behalf. Only 27% are comfortable with unlimited AI spending authority. Thirty-six percent say they would trust an AI agent backed by their bank. Twenty-eight percent would trust an independent agent. The paper's own summary: "Trust is the adoption switch." This is empirical confirmation of something that was structurally obvious. The infrastructure to move money is almost ready. The infrastructure to decide whether money should move does not exist. The asymmetry Two days ago, the x402 Foundation launched under the Linux Foundation. Twenty-two founding mem
I just shipped my first major update to a Chrome extension. Here's what I changed and why.
Building in public means being honest about mistakes. Here's one I made with Prompt Helix and how I fixed it in v1.0.2. Prompt Helix is a Chrome extension that extracts webpage content and sends it directly to your chosen AI. No copy-pasting. No tab switching. Click, ask, get an answer in context. I launched it in February and have been iterating since. The mistake I made with the free tier. When I launched I gave away too much for free. OpenAI and Claude completely free with no daily caps. It felt generous and user-friendly. In reality it meant there was no reason to ever create an account or pay. Someone could install it and use it every day forever without seeing a single upgrade prompt. Classic freemium mistake. I only realised this when I looked at my Clerk dashboard and saw 60 instal
How Cloud-Based Data Systems Are Transforming Businesses
Introduction In today’s digital-first world, businesses are generating more data than ever before. Managing this data efficiently has become a critical challenge—and opportunity. Traditional on-premise systems are no longer sufficient to handle the scale, speed, and complexity of modern data needs. This is where cloud-based data systems come into play. By offering scalable storage, real-time processing, and cost-effective infrastructure, cloud technologies are revolutionizing how businesses operate, innovate, and grow. What Are Cloud-Based Data Systems? Cloud-based data systems refer to platforms and services that store, manage, and process data over the internet instead of local servers. These systems allow businesses to access their data anytime, anywhere, without the need for heavy phys
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I just shipped my first major update to a Chrome extension. Here's what I changed and why.
Building in public means being honest about mistakes. Here's one I made with Prompt Helix and how I fixed it in v1.0.2. Prompt Helix is a Chrome extension that extracts webpage content and sends it directly to your chosen AI. No copy-pasting. No tab switching. Click, ask, get an answer in context. I launched it in February and have been iterating since. The mistake I made with the free tier. When I launched I gave away too much for free. OpenAI and Claude completely free with no daily caps. It felt generous and user-friendly. In reality it meant there was no reason to ever create an account or pay. Someone could install it and use it every day forever without seeing a single upgrade prompt. Classic freemium mistake. I only realised this when I looked at my Clerk dashboard and saw 60 instal
Linear Space Streaming Lower Bounds for Approximating CSPs
arXiv:2106.13078v4 Announce Type: replace-cross Abstract: We consider the approximability of constraint satisfaction problems in the streaming setting. For every constraint satisfaction problem (CSP) on $n$ variables taking values in $\{0,\ldots,q-1\}$, we prove that improving over the trivial approximability by a factor of $q$ requires $\Omega(n)$ space even on instances with $O(n)$ constraints. We also identify a broad subclass of problems for which any improvement over the trivial approximability requires $\Omega(n)$ space. The key technical core is an optimal, $q^{-(k-1)}$-inapproximability for the Max $k$-LIN-$\bmod\; q$ problem, which is the Max CSP problem where every constraint is given by a system of $k-1$ linear equations $\bmod\; q$ over $k$ variables. Our work builds on and ext
Faraday Future Announces Its Latest Robot, the FX Aegis Quadruped, has Completed Its Full Compliance Certification in the United States - StreetInsider
Faraday Future Announces Its Latest Robot, the FX Aegis Quadruped, has Completed Its Full Compliance Certification in the United States StreetInsider
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