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‘We Will Fight to Our Very Last Breath:’ Township Leaders Vow to Fight Nuclear AI Data Center


Board members of a small township in Michigan agreed to “fight to our very last breath” against an AI data center planned in their community. America’s nuclear scientists and the University of Michigan want to build a massive data center in Ypsilanti Township, Michigan. If built, the data center will, among other things, run simulations to help America build nuclear weapons.The residents of Ypsilanti Township overwhelmingly oppose the construction of the data center and voiced their opposition to the computer warehouse during a public board meeting on June 16. In a show of support that’s often rare from local leaders in communities with data centers, Ypsilanti Township’s board vowed to fight UofM and Los Alamos National Laboratory, which is partnering with the university, with everything they had.

Throughout most of the three hour board meeting, a photograph from a data center groundbreaking in nearby Saline Township was projected onto a wall behind the board. The photo showed a grinning Michigan Governor Gretchen Whitmer standing in line with Oracle CEO Clay Magouyrk. It was taken at the June 1 groundbreaking of an Oracle and OpenAI data center in nearby Saline Township, one of several Stargate projects. Saline Township is a community of only 2,300 people and the fight against the data center was so contentious that the Township treasurer resigned in tears during a public meeting in May.

During the groundbreaking, a videographer caught Whitmer talking with Magouyrk. In the video Whitmer appeared to tell the billionaire, “We’re used to people saying no, and doing it anyway.” Whitmer’s office has officially denied she said that, but many of the residents of Michigan—including the people of Ypsilanti Township—believe she did.Governor Whitmer had a hot mic moment at the Saline Data Center groundbreaking, where she tells Oracle CEO Clay Magouyrk, “We’re used to people saying f*ck no, and doing it anyway.” I’m old enough to remember when she doxxed Marshall constituents who opposed her BlueOval project. pic.twitter.com/PRFnjGY5l9— Heather Dow (@PatriotPostGirl) June 8, 2026
Cilla Cresswell shot the video of Whitmer and was present at the Ypsilanti Township board meeting on Tuesday. “On June 1 I was standing just to the left, right there,” Creswell said, referring to the photo that loomed behind the board during the meeting. “I was there. I recorded that clip (… ) I was right there. And they want to say it’s fake, but I just want to let you guys know it’s real. You can play it on my camera.”Members of the board and the community referenced the photograph often during the meeting. “You have people in that photograph worth billions of dollars. Not just millions, we’re talking trillions. Soon to be trillionaires. Yet this state, in its zeal to become the data capital of the country, has extended unprecedented tax credits to the richest corporations in the world,” Douglas Winters, a lawyer representing Ypsilanti Township, said in the meeting.“Having to stare at this picture during this meeting has my blood boiling,” said Ypsi resident Laura Witowski. “I did not realize how emotional I would be. The waste of space. The complete lack of regard for humans and animals and for what?”During the hours of community comments, residents stepped forward to voice complaints that have now become common about data centers in America. The people of Ypsilanti Township worried about the rising cost of electricity, how much water the building will use, and how noisy the data center would be once finished.They also called on the Township board to do everything in their power to stop it from even being built. “Put yourselves on the line. Those people will listen to you better than they will listen to us. Please put yourselves, your jobs, and your comfort on the line to stop this for us,” Ypsi resident Jane Wolf said. “Get creative. Tear up the road. Block the road. Break the law. Do whatever you need to do for us. You will be remembered better in history for the job that you did if you can get creative and really put yourselves out there.”Jill Warren, the wife of a Methodist pastor, suggested residents brush up on the OSS’ Simple Sabotage Field Manual. “Simply slow things down bureaucratically,” she said. “Make sure we block where we can. Use very slow agendas and response times and do, within your power, the work that you are entitled to do. For those who aren’t familiar with it, please look up the Simple Sabotage Field Manual and use it in your own lives of action as well (…) they may not care about us, but we care about us and we’re here and we’ll continue to be here and support the work that you’re doing on our behalf.”Alyssa, an Ypsilanti resident, cited long passages from John Hershey’s Hiroshima—a 1946 book that focused on the victims of the first atomic bombing. “We don’t need simulations to know what a nuclear strike looks like,” she said. “We have pictures, videos, and audio of what happens. We know what it does to bodies. We know what it does to children and what it does to life.”

Board supervisor Brend Stumbo vowed to fight. “This is going to harm our community in our future. We will fight to our very last breath, but we need help. And we need it from the people who have the power to stop things,” she said.Stumbo explained that, early on, she and other members of the board were ignorant about data centers and that she was grateful to the Township’s residents for informing her. “Now we know and we’re thankful for the residents and non-residents that came to our meetings early and told us, ‘don’t trust UofM,’” she said. “We do not love nor do we appreciate what the board or regents is doing to our community. It needs to stop. And everyone that showed up here today, we greatly appreciate it and we will keep going, like everyone has said, by doing it together (…) I will stand with you. I will fight with you. And I know this entire board and our Township attorney will as well. So let’s keep doing it together.”The Township has, so far, made good on its word and it’s been creative in its opposition. In April, the board voted to institute a 365 day moratorium on supplying water to data centers so it could conduct a scientific study into how hyper scale data centers might affect the community water supply. In response, UofM threatened to sue and claimed that withholding water from an AI data center meant to power nuclear weapons research was unlawful discrimination.

About the author
Matthew Gault is a writer covering weird tech, nuclear war, and video games. He’s worked for Reuters, Motherboard, and the New York Times.





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I Tracked LLM Pricing for 8 Weeks. Here’s What the Data Shows.



The Problem That Started ThisA few months ago, I was building an AI product and hit a wall: Which LLM should we use?The question sounds simple. But the pricing landscape for AI models shifts constantly and without warning. OpenAI has 69 models listed on their pricing page. Google has 18. Anthropic launched three new Claude versions in the span of weeks. By the time I had compared options and made a decision, I had no confidence the numbers were still current.I checked pricing pages. I checked docs. I found no single place that told me:What did this cost last week vs. today?Which providers actually changed their prices recently?How wide is the spread for comparable models?So I automated it. Starting April 24, 2026, I built a daily scraper that pulls pricing data from every major provider. Here is what 8 weeks of data actually shows.1,111models tracked33providers59days of data5price changes detectedFinding 1: The Big Providers Did Not MoveThe headline finding is not dramatic: Anthropic, OpenAI, Google, Mistral, and xAI all held their prices flat for the entire 59-day period. Not a single price change detected across those five providers.That is useful information on its own. If you are budgeting around these providers, your cost model from April is still accurate today.Here is the current pricing snapshot for the most-used models, accurate as of June 22:ModelInput / 1M tokensOutput / 1M tokensNoteopenai / gpt-4-turbo$10.00$30.00Stable since Apr 24openai / gpt-4o (chatgpt-4o-latest)$5.00$15.00Stable since May 12anthropic / Claude Sonnet 4.5$3.00$15.00Stable since Apr 24anthropic / Claude Opus 4.5$5.00$25.00Stable since Apr 24anthropic / Claude Haiku 4.5$1.00$5.00Stable since Apr 24google / Gemini 2.5 Pro$1.25$10.00Stable since Apr 26google / Gemini 2.5 Flash$0.30$2.50Stable since Apr 26google / Gemini 2.0 Flash$0.10$0.40Stable since Apr 26mistral / Codestral$1.00$3.00Stable since Apr 24xai / Grok 4.3$1.25$2.50Stable since May 16For teams budgeting: The major closed-model providers are behaving predictably right now. Your April cost model is still valid. That said, 8 weeks is a short window. Pricing for these providers has historically shifted without notice.Finding 2: The Pricing Spread is EnormousThe bigger story is not volatility. It is the 600x price range that now exists across the tracked catalog, from sub-cent inference to frontier flagship models.ModelInput / 1M tokensOutput / 1M tokensNotegroq / llama-3.1-8b-instant$0.05$0.08Cheapest trackeddeepseek / deepseek-v4-flash$0.14$0.28google / Gemini 2.0 Flash$0.10$0.40deepseek / deepseek-v4-pro$0.44$0.87xai / Grok 4.3$1.25$2.50anthropic / Claude Sonnet 4.5$3.00$15.00openai / gpt-4-turbo$10.00$30.00openai / gpt-5.4-pro$30.00$180.00Highest-cost frontier trackedGroq’s Llama 3.1 8B costs $0.05 per million input tokens. GPT-4 Turbo costs $10.00 (200x). GPT-5.4 Pro costs $30.00 (600x). All three are in our dataset today. DeepSeek V4 Pro at $0.44 per million input tokens consistently ranks near the top on reasoning benchmarks at a fraction of the flagship price.The question teams should be asking is not just “which model is best?” but “which model is best for this specific task given the cost?” For many production workloads, the answer is not the model you started with.Real cost difference: A team running 100M input tokens per month on GPT-5.4 Pro spends $3,000. The same usage on GPT-4 Turbo costs $1,000. On DeepSeek V4 Pro it is $44. On Groq’s Llama 3.1 8B it is $5. The right answer depends entirely on what the task requires, but most teams never run this comparison after their initial model choice.Finding 3: All 5 Price Changes Came from One ProviderOver 59 days, our scraper detected 5 pricing changes across all 1,111 models. Every single one was on Together AI, a hosting aggregator that runs third-party open-source models.DateModelBeforeAfterChangeMay 27qwen37-max$2.50 / $7.50$1.25 / $3.75-50%Jun 2Qwen3.5-9B$0.10 / $0.15$0.17 / $0.25+70%Jun 2Llama-3.3-70B-Turbo$0.88 / $0.88$1.04 / $1.04+18%Jun 2Meta-Llama-3-8B-Lite$0.10 / $0.10$0.14 / $0.14+40%Jun 17DeepSeek-V4-Pro$2.10 / $4.40$1.74 / $3.48-17% / -21%The biggest move: Qwen37-max dropped 50% overnight on May 27, with no public announcement that reached mainstream channels. Teams running that model through Together AI saw their costs cut in half. Teams not monitoring pricing had no idea.Three models saw price increases on June 2: Qwen3.5-9B (+70%), Llama-3.3-70B-Turbo (+18%), and Meta-Llama-3-8B-Lite (+40%). Not all pricing movement favors the buyer.Why this matters: None of these changes came with direct user notifications. No email, no in-dashboard alert, no API changelog. The only way to know was to check the pricing page, which almost nobody does after the initial setup.Finding 4: No Provider Notifies You DirectlyAcross all 5 detected changes, the announcement path was the same: nothing sent directly to users. One change (DeepSeek-V4-Pro via Together) appeared in a provider blog post days later. The rest were silent.Compare that to how other infrastructure pricing works:AWS sends email notifications for pricing changes to affected customersStripe gives 30 days notice before any fee changesTwilio posts a public changelog and emails account ownersLLM providers are operating more like spot markets than enterprise software. Prices move when they move. Most teams find out on their invoice.What I BuiltAfter a few weeks of running this manually, I automated it and opened it up. Token Prices tracks 1,100+ models across 33 providers daily and surfaces changes the moment they happen.The tool gives you:1A live pricing dashboard across all tracked providers and models2A price change feed showing every detected move with before/after prices3Historical data going back to April 24, 2026 (the full dataset)4A REST API so you can pull pricing into your own FinOps toolingThe free tier covers the 10 major providers. Paid plans add historical depth, more providers, and API access. tokenprices.ioOpen Questions1.Are there pricing changes I missed? If you spotted a move that did not show up in this data, I want to know.2.Which providers should I add next? The scraper can cover more platforms. What is on your list?3.How do you handle model selection today? Dashboard? Spreadsheet? Gut feeling?4.What would make this data actionable for your team? Alerts? Cost projections? A comparison view?Let us know at support@tokenprices.ioData note: All figures come from publicly available pricing pages scraped daily from April 24 to June 22, 2026. No private APIs or negotiated rates are used. Prices reflect standard on-demand tiers. All amounts are per 1 million tokens unless noted.



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av29nassh-sketch/PreFlight: The local security gate for AI-generated code. · GitHub



Stop AI Coding Drift before it becomes production technical debt. PreFlight is a local-first safety gate for AI-generated code, built to catch unsafe auth, RLS, SQL, SSRF, command execution, dependency, and secret-handling changes before they get committed.
Website: https://preflight-vibe.vercel.app
Choose Your Remediation Depth
PreFlight runs in two distinct tiers depending on what your codebase needs.
Free Tier: PreFlight Guardian

What it does: Unlimited local scanning plus 10 free patch applications across local deterministic fixes and proxy-backed AI fixes.
Setup: Zero config for scanning. A Pro key is only required after the 10 free patches are used.
Commands:

npm install -g preflight-pro
preflight init
preflight scan . –fix
Installing preflight-pro exposes the universal preflight command in your shell.

What it does: Unlimited scans and unlimited fixes, including deep reasoning remediation for complex multi-file architectural flaws, tenant isolation logic, and parametric SQL injections.
Setup: Requires an active PREFLIGHT_PRO_KEY or a saved key from preflight auth.
PowerShell:

$env:PREFLIGHT_PRO_KEY=”PREFLIGHT-BETA-XXXXX”
preflight scan . –fix

export PREFLIGHT_PRO_KEY=”PREFLIGHT-BETA-XXXXX”
preflight scan . –fix

PreFlight supports both a terminal-first workflow and an IDE-first workflow. Both paths end with preflight init, because that wizard connects your editor, MCP clients, and Pro/Beta key in one place.

npm install -g preflight-pro
preflight init
Then scan any project from its root:

Install the global CLI command. The VSIX gives you the in-editor UI, but the extension still uses the global preflight command to start The Eye daemon and run fixes.

npm install -g preflight-pro

Download and install the PreFlight Companion VSIX extension:

Run the setup wizard once:

Open your project in the IDE. The extension starts The Eye automatically, watches file saves, and surfaces PreFlight alerts in-editor.

The Eye: The VS Code/Cursor extension starts PreFlight’s local daemon automatically. It watches file saves and raises in-editor alerts when AI-generated code introduces a hard-block issue.
MCP bridge: preflight init can also wire preflight mcp into supported AI editors so agents can call PreFlight tools without leaving the coding flow.

Free users get unlimited scans and 10 total patches across local fixes and proxy-backed AI fixes. After the 10 free patches are used, unlimited fixes require a Pro/Beta key.
You can add your key during preflight init, or activate it directly:
preflight auth PREFLIGHT-BETA-XXXXX
For one terminal session, you can also set it manually:
$env:PREFLIGHT_PRO_KEY=”PREFLIGHT-BETA-XXXXX”
export PREFLIGHT_PRO_KEY=”PREFLIGHT-BETA-XXXXX”

Free Tier: Unlimited scans, 10 Free Patches (Local + Deep-Reasoning AI).
Solo Pro: $19/mo for unlimited scans and fixes.
Teams: $49/seat/mo for team rollout, shared onboarding, and unlimited scans and fixes.

PreFlight is now powered by deeper local analysis primitives:

Micro-Fuzzer: Generates focused security payloads for risky data-flow paths, such as SQL injection, command injection, auth bypass, SSRF, and path traversal.
Quantized CPG (Code Property Graph): Builds a compact in-memory graph of syntax, control flow, and data flow so PreFlight can trace untrusted input into dangerous sinks instead of relying on brittle string matching.
The Eye daemon: Runs locally through the CLI/extension workflow and watches file saves so issues appear while the AI coding session is still active.

Tri-State Risk Score Engine
This is the core PreFlight signal. Every scan resolves into one of three clear outcomes so you know whether to stop, review, or ship.

Score
Meaning
What It Catches

🔴 Hard Block
Stop immediately. This change is unsafe to ship.
Exposed frontend secrets, leaking database service roles, command execution, SQL injection, or missing Supabase Row Level Security (RLS).

🟡 High-Risk Drift
Review carefully. The code may be structurally wrong even if it runs.
Structural state inconsistencies, un-idempotent webhooks, weak validation, or open CORS contexts.

🟢 Pass
Safe to continue. No blocking structural risk was detected.
Standard local edits matching your expected stack rules.

PreFlight runs fixes in a strict sequence:

Phase 1: Offline Local AST Sweep
PreFlight completes an ultra-fast offline structural pass first and applies any deterministic local fixes it can resolve safely.
Phase 2: PreFlight Pro Deep Reasoning Handoff
Remaining SQL, fuzzer, and complex architectural flaws are handed off through the secure proxy-backed reasoning path when a patch requires deeper context.

The first 10 patch applications are free across both phases. After that, a PREFLIGHT_PRO_KEY is required.

PreFlight can run directly in the terminal, through the VS Code/Cursor extension, or as an MCP server for AI-native editors.
Start the MCP server locally:

Available MCP tools include:

scan_project
preflight_fix
audit_dependencies

scan_project remains free and unlimited. preflight_fix shares the global 10-patch free allowance before a PREFLIGHT_PRO_KEY is required.
Post-Fix Verification Loop
PreFlight is designed to be used as a closed loop, not a one-shot scanner:

Generate or modify code with your AI coding assistant.
Run preflight scan . to classify the change under the Tri-State Risk Score.
If PreFlight returns Hard Block, stop and repair the structural issue before moving forward.
If PreFlight returns High-Risk Drift, run preflight scan . –fix and inspect every proposed fix before applying it.
Re-run preflight scan . after each accepted fix to confirm the repository settles into Pass.
Ship only after the final verification pass is green and the structural receipt matches the architecture boundary you intended.

This verification loop is the product: scan, review, patch, re-scan, then deploy with confidence.



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