标签：#gas

Meta has made significant investments in natural gas over the past year. Now it's dropping out of an industry renewable energy group.

How Normal Software Engineers Actually Use AI in Their Daily Work Let's cut through the hype. You're not building the next AGI. You're a working software engineer with deadlines, legacy code, and a backlog that never shrinks. So how do you actually use AI tools in your day-to-day work? After surveying hundreds of developers and reflecting on real-world usage patterns, here's what normal software engineers are doing with AI—no Silicon Valley theatrics required. The Mundane But Invaluable: Code Completion and Boilerplate The most common use case is the least sexy: letting AI handle repetitive code. GitHub Copilot, Cursor, and similar tools excel at generating boilerplate that you'd otherwise copy-paste from Stack Overflow or previous projects. Real example: Writing CRUD endpoints in Express/TypeScript: typescript // Type this comment and let AI complete: // Create a REST endpoint for user registration with email validation app.post('/api/users/register', async (req: Request, res: Response) => { try { const { email, password, name } = req.body; // Email validation const emailRegex = /^[^\s@]+@[^\s@]+\.[^\s@]+$/; if (!emailRegex.test(email)) { return res.status(400).json({ error: 'Invalid email format' }); } // Check if user exists const existingUser = await User.findOne({ email }); if (existingUser) { return res.status(409).json({ error: 'User already exists' }); } // Hash password and create user const hashedPassword = await bcrypt.hash(password, 10); const user = await User.create({ email, password: hashedPassword, name }); res.status(201).json({ userId: user.id, email: user.email }); } catch (error) { res.status(500).json({ error: 'Internal server error' }); } }); Did AI write perfect code? No. But it gave you scaffolding to refine, saving 10-15 minutes of typing. That's the real win. The Game-Changer: Explaining Legacy Code and Obscure APIs Every developer inherits someone else's mess. AI tools shine when deciphering undocumented code or unfamiliar libraries. Pract

Applied Computing has raised a $20M Series A to build a foundation AI model for the oil, gas and petrochemical industry.

The amendment would restrict building codes that promote electrification.

A government customer of NSO Group used the company's Pegasus spyware to hack into the phone of a European politician, who at the time was serving on an EU committee tasked with investigating the spyware industry.

Last time I wrote about using glasp, a Go-based, npm-free CLI for Google Apps Script (GAS), in GitHub Actions. Previous post: Lean, Fast, Simple — npm-free GAS Deployment on GitHub Actions with glasp This time, a quick rundown of what landed in v0.3.0 and v0.4.0 . v0.3.0: PKCE support glasp login now supports PKCE (RFC 7636) as an opt-in. glasp login --pkce # or GLASP_USE_PKCE = 1 glasp login Each login generates a code_verifier and sends an S256 code_challenge to Google. It's a defense against authorization code interception, and it coexists fine with the existing client_secret flow. It only applies to the interactive login — --auth / GLASP_AUTH for CI is untouched. Off by default. Worth turning on if you're in a stricter security environment. v0.4.0: Timeouts and retries The focus here is basically "can this run unattended in CI/CD without falling over." Timeouts Script API requests previously had no timeout — a stuck request could hang the job indefinitely. v0.4.0 adds a 180s default. glasp push --timeout 60 # set to 60s glasp push --no-timeout # disable Also configurable via GLASP_TIMEOUT / GLASP_NO_TIMEOUT env vars or timeoutSeconds in .glasp/config.json . Priority: --no-timeout > flag/env > config > default. If the config file is broken, it warns instead of silently falling back. Retries Transient failures (5xx, 429) now get retried automatically. glasp push --max-retries 5 glasp push --no-retries 3 retries by default (up to 4 attempts total) Only applies to idempotent commands: push , pull , clone , list-deployments Commands with side effects ( create-script , run-function , etc.) are never retried Exponential backoff with jitter, respecting Retry-After It's implemented as a single http.RoundTripper wrapper, so the Google SDK itself isn't touched — same pattern as the timeout implementation. retryTransport → oauth2.Transport → http.DefaultTransport Some refactoring, too Internal packages got reorganized ( #107 ), and the hand-rolled retry transport was swappe

Gov. Ron DeSantis calls it a crackdown on "radical climate policies."

Microsoft inked a 20-year power purchase agreement with Chevron, locking in decades of carbon emissions from a new natural gas power plant.

SpaceX's AI1 satellite spans 70 meters tip-to-tip — wider than a Boeing 747 — and it exists entirely to run AI inference in low Earth orbit. Elon Musk posted the reveal video to X on June 9, 2026, ahead of SpaceX's IPO, with a three-word summary: "much simpler than Starlink." Each satellite produces 150 kW of peak AI compute and 120 kW sustained. SpaceX's roadmap calls for 1 GW of orbital AI compute capacity by late 2027, which at 150 kW per satellite means manufacturing roughly 6,700 AI1 units per year. To hit that number, they are building an 11-million-square-foot facility in Bastrop, Texas called Gigasat — nearly twice the floor area of Tesla's Gigafactory Nevada, dedicated to satellite production. The question is not whether the engineering works. SpaceX has launched more than 7,000 Starlink satellites. The question is whether orbital AI compute makes economic sense at scale, and that question nobody has answered publicly yet. The Reveal Wasn't Accidental SpaceX filed for its IPO at approximately $75 billion valuation in early June 2026. Musk's June 9 reveal of AI1 arrived within days of that filing. Orbital AI compute is the narrative SpaceX needs to justify a valuation that goes beyond launching satellites for other people. Every terrestrial cloud provider — AWS, Google Cloud, Azure — is competing for land, power, and cooling capacity to support the next generation of frontier AI. Musk's pitch is that those three constraints don't exist in space. The physics backs him up. The economics remain unproven. Why Space Has Structural Advantages for AI Compute The AI1 satellite's design exploits two physical realities that are impossible to replicate on Earth. Power is essentially free. In a sun-synchronous LEO orbit, a satellite receives near-constant solar illumination. SpaceX's solar arrays achieve 250 W/m² power density without atmospheric attenuation. The marginal cost of electricity after the capital investment in the array is close to zero — no grid contracts,

WhatsApp disrupted spear phishing attempts, asks court to hold NSO in contempt.

Mike Schroepfer's Gigascale Capital has raised a large fund to back founders building climate-friendly solutions for the world's energy and material shortages.