Record home battery installations unlock options for grids—and AI data centers.

Selling server infrastructure would put Meta in competition with Amazon and Google.

Turn 1 creative into every ad format, instantly Discussion | Link

An optimal ratio of 10-15 grams of larvae per gram of specimen minimized cleaning time with no bone damage.

Ever wondered how it works? Have you ever used Opay for a transfer and thought ,"Wow, that was fast and it barely takes one mintue to see alert. Or imagine an artist in Lagos, Nigeria dropping a new album and fans in London, Accra, and New York can stream it instantly, without the artist having to own a room full of servers with blinking wire. That is the magic of * cloud computing * Cloud computing is the * on-demand delivery of IT resources over the internet. * The servers,storage,databases, networking are called resources, which are rented instead of being bought physically. You pay only for what you use, like NEPA prepaid. No huge capital expenditure, just operational expenditure. Companies like AWS, Microsoft Azure,and Google Cloud Platform run the gaint computer rooms for you What Makes Cloud Powerful ? Scalability: The manual growth Imagine your app suddenly gets 10,000 users ? you can manually upgrade your resources to handle it. ** Elasticity:** The automatic growth The system scales itself up in real time based on traffic.No humnan needed. Agility: Move fast Test an idea today,launch tomorrow. you can create ,configure, and delete databases or servers in minutes, not weeks. High Availablity: Always On Cloud provider guarantee 99.9% uptime. Even if one server fails,your app stays live. ** Fault Tolerance: Built to survive ** If one component breaks,others take over automatically.Your services keep running. ** Global Reach: Be Everywhere,Fast** Deploy your app to servers in Europe, America or Asia with one click. This is how musicans album are instantly closer to fans worldwide. What powers Cloud Computing * Virtualization * Virtualization lets one physical server act like many "virtual server" or VMs A software called** hypervisor** separates the software from the physical hardware. So 20 companies can rent part of the same machine without knowing it. Is Cloud Safe and Reliable ? Yes. Compared to keeping a server in your offie, cloud is safer. Big provider

SpaceX reportedly showed investors a "handset-like" AI device before going public. It could be another signal SpaceX wants to expand into wireless.

Vendor onboarding usually starts with one clean request and then turns into a messy thread. Procurement asks for a W-9, security asks for a SOC 2 report, finance asks for remittance details, legal asks for an executed agreement, and the vendor replies with four attachments across three messages because different people own different parts of the process. That is exactly the kind of workflow where a generic "AI email assistant" gets risky. You do not want a model improvising legal language, requesting bank details in the wrong channel, or forwarding a confidential report to the wrong internal alias. You want the agent to own the repetitive coordination while your application keeps the state machine, policy, audit log, and approvals. The pattern I reach for is a dedicated Nylas Agent Account: vendors@yourcompany.com . It is a real mailbox the onboarding agent owns. It receives the vendor's replies, detects what is attached, updates your vendor record, sends safe reminders, and escalates missing or sensitive items to a human. The agent is not borrowing an employee's inbox, and it is not scraping a shared procurement mailbox. It has a grant, an email address, webhooks, threads, folders, and the same Messages API you would use for any other mailbox. I work on the Nylas CLI, so the terminal examples below use the commands I would use while building and debugging this flow. I also include the raw API calls because the production version belongs in your service, not in a shell script. What the agent should own Start by drawing the boundary tightly. A vendor onboarding agent should own message handling and coordination, not business approval. Good responsibilities: Receive vendor replies at a stable address. Read message bodies and attachment metadata. Match a reply to an existing vendor record. Detect which onboarding items are complete, missing, expired, or unreadable. Draft reminders and status updates. Schedule handoff calls when the vendor asks for help. Escalate sensit

Hi everyone. Do the ACL arr may 2026 reviews come out of July 2nd or do they come out on July 7 th?? How much does one need to get into Main or Findings? I am a bit new to this. Thanks a lot folks. submitted by /u/Anshuman3480 [link] [留言]

The actor and investor is joining forces with Morgan Beller, who was previously a GP at NFX, to invest in early-stage startups.

Building an AI agent is fun. Fixing its production latency when it's juggling live data, RAG, and text-to-speech? Not so fun. In the latest episode of the AI Agent Clinic, we sat down with developer Sami Maghnaoui to debug PlaybackIQ, a football / soccer agent he built to provide pre and post match analysis with text to voice, and minute-by-minute match insights with interactive UI. The app was awesome, but under heavy "match day" data loads, the wait times were killing the UX. Here’s how we fixed it: The Bottleneck: We implemented OpenTelemetry on the Agent Platform to trace exactly where the LLM calls and data retrieval were hanging up. The Scale: We shifted the deployment to Cloud Run to properly handle concurrent traffic. The Result: We managed to slash the agent's latency by 80%. If you're dealing with sluggish LLM response times in your own apps and want to see what a production-grade fix looks like, we recorded the whole teardown and rebuild. 🎥 Watch the teardown here: [ https://youtu.be/G7olcqETSn8 ] (Let me know in the comments what your go-to stack is for tracing LLM latency!)

The problem no one was solving Every Algerian developer building with AI hits the same wall: an international payment card. OpenAI, Anthropic, Google — every major AI provider assumes you have one. Most Algerian developers don't, or don't want to deal with the friction of currency conversion, card rejections, and unpredictable billing in a foreign currency. That's not a minor inconvenience. It's a barrier that quietly excludes an entire generation of developers from building with the best AI models available — not because they lack the skill, but because of infrastructure that was never designed with them in mind. The vision: AI sovereignty, not just AI access Access alone isn't the goal. The goal is sovereignty — Algeria having its own AI infrastructure layer, controlled locally, billed locally, and built to local compliance standards, instead of depending entirely on foreign gateways with no local accountability. That's what DEVUP AI is: Algeria's first AI inference gateway, built from the ground up to remove every friction point between an Algerian developer and the AI models they need. What DEVUP AI actually does 170+ AI models — including DeepSeek V4, Llama 3.1 405B, Qwen 3, Gemma 2, Mistral, GPT, Claude, and Gemini — through a single API OpenAI-compatible and Anthropic-compatible — point your existing SDK at our endpoint, no code rewrite needed Local DZD billing via Edahabia/CIB — no international card required SATIM-certified payment infrastructure — full compliance with Algeria's national payment standards Scoped JWT authentication for production-grade security A dedicated SDK ( npm install devupai ) and full documentation, so integration takes minutes, not days The technical bar was non-negotiable: this had to be production-grade from day one, not a side project. SATIM certification alone meant building proper transaction validation, receipt generation, chargeback tracking, and rejection-rate monitoring — the same rigor a bank would expect from a payment pr

“We will own nothing, it's truly sad.”

I wrote a detailed comparison of GitHub Actions vs Jenkins after working with both while learning DevOps. Instead of focusing on "which one is better," I looked at questions like: When does GitHub Actions become enough? When is Jenkins still the right choice? Performance and scalability Security and maintenance Cost Real-world use cases I'd love to hear where you disagree or what your production experience has been. Article: actions vs jenkins submitted by /u/ganeshak11 [link] [留言]