Private and encrypted. Maple builds your product, audits your code, and scans for vulnerabilities. Privacy by design.
Private AI →
Joined February 2025
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Maple AI retweeted
The AI Crash Last Week Was Sniffing Out Something BIG xitter.twitterapi.xyz/i/broadcasts/2AMPPoEJa…
Big move from Google. Chips built so even an insider can't access your data while AI runs.
This should be the standard. Maple already works this way, and you can verify it yourself.
Today, we're expanding our eighth-generation TPU portfolio with two new systems built specifically for the agentic era — bringing our total to four distinct eighth-generation TPU systems launched in a single year.
TPU 8i Max was built for massive context windows and the highest compute density per rack, and TPU 8tx is optimized for secure and confidential inference. While flexible across workloads, the four systems in our 8th gen TPU portfolio give developers and organizations a purpose-built accelerator for every stage of the agentic lifecycle.
@AminVahdat, SVP and Chief Technologist, AI and Infrastructure, explains why we're expanding our TPU portfolio and what everyone needs to know about TPU 8tx and 8i Max ⬇️
Maple AI retweeted
Cyberattackers don't ask for permission.
Defenders shouldn't be met with "I can't help with that."
Get private superintelligence in your pocket.
10% off your first 3 months of Maple with code FREEFELIX
maple.ai/pricing?utm_source=…
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We baked Felix a cake.
🔒🚨 NO NORD NOVEMBER IS HERE 🚨🔒
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NEW: Obscura is now offering seven-day free trials.
Start a 7-day free trial, buy one month, send proof of time left on your current plan, and we’ll match it for free (up to 2 years).
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What changed from K3, what it takes to run it yourself, and how to use it in Maple 👇
maple.ai/blog/kimi-k3-1-pro-…
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Thanks @TinfoilAI for getting Kimi K3.1 Pro running in secure enclaves so quickly after the weights dropped 🩶 It's live in Maple now.
An open-weight model within a point of Claude Opus 5.5 on agentic coding is now in Maple.
Kimi K3.1 Pro from @Kimi_Moonshot, running in attested secure enclaves, so no third party can read your chats.
In Maple Chat and Maple Work, on Pro, Max and Team.
Near-frontier. Open weights. Private.
The privacy advantage is clear if you own the hardware. It's less obvious if you're renting the compute.
That's where attestation helps: you can check what's running instead of taking the host's word for it.
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Cost is why many teams are moving to open models.
The next question is where the prompts go, and who can read them along the way. That's what attested enclaves are for.
BREAKING: Revolut moved ~2,000 engineers onto self-hosted GLM for coding and pushed Claude Code and Codex to the exception list.
Per David Abitbol, who leads AI ops there: 56 Nvidia B200s, a blended 30 cents per million tokens, roughly a tenth of what they paid Anthropic and OpenAI. Engineering lead time improved 70%.
Here's the part that matters: the gains showed up when tokens stopped being rationed. Engineers quit saving AI for the hard tickets and pointed it at everything.
Frontier models become the exception, open weights become the default. That's a pricing problem for every lab heading to IPO.
h/t @OliverMolander
Would you move your team off frontier APIs if the bill dropped 90%?
