AI of the week: @usedotai
DOT processed 20.1B tokens over the last 30 days.
Paid subscriptions grew 3x faster than daily free users.
- GPT-6.1 Sol runs privately across Chat, Agent Chat, DotCode, and the API.
- The model carries a 1.05M-token context window.
- Dot Desktop handled a FreeCAD and PrusaSlicer workflow from one request.
- The workflow created a usable 3D-print file without dedicated connectors or scripts.
- Another $46K went into infrastructure, taking total infrastructure spend above $160K.
- Eight NVIDIA B300 GPUs now run MiMo V2.6 Pro on Dotâs own infrastructure.
The announced staking model links $DOT rewards to inference credits.
The AI yield range starts at 6% and reaches 16% as monthly profit grows.
Private inference, owned compute, and agent execution are moving into one AI economy on Base.
Nouvelle prise de position sur @base, sur un projet qui me semble totalement sous-valorisĂŠ et surtout sous les radars.
> @usedotai et son token, le base:0x23a2847d772803f9efc64b4277b782b06296fe51
Câest une plateforme dâinfĂŠrence IA axĂŠe sur la privacy. Les utilisateurs alimentent leurs crĂŠdits en USDC ou en $DOT et exĂŠcutent des modèles privĂŠs sans conservation des prompts.
Les $DOT dĂŠpensĂŠs pour lâinfĂŠrence sont burn. RĂŠsultat ?
~11,92 % de la supply burn
Oui, la plateforme est utilisĂŠe, et de manière très organique. Le marketing nâa pas commencĂŠ.
> Environ 4 000 utilisateurs daily / 189 subscriptions payantes / ~$9.8k MRR
Metrics : https://t.co/jSlxPtQJjs
Metrics : https://t.co/vDsIK3DDBj
Pourquoi utilisent-ils @usedotai ? Tout simplement parce quâils sont moins chers que les autres, Ă lire : https://t.co/mxsHKx0bbz
Ils passent la deuxième sur le marketing, rdv le 4 septembre sur lâun des meilleurs podcasts du moment @MCGlive : https://t.co/MTvwbGnJaY
En tout cas, certaines personnes semblent savoir des choses, comme ce wallet : https://t.co/JbY75pJnt0
Ou celui-ci : https://t.co/ax2HjfomNy
Seulement 2.3M de market cap, pas besoin de vous dire que câest risquĂŠ et très volatile.
Je pense que la liquiditĂŠ va revenir sur Base et quâon aura le droit Ă de beaux pumps.
Cette comparaison entre $VVV et $DOT est très bullish, sachant que ce dernier est valorisÊ à plus de 1.3bn de FDV.
$DOT a une très belle chart avec de bons volumes, je trouve le R/R excellent.
Je ne suis personne, faites vos recherches, et si ce genre dâanalyse vous plaĂŽt, faites-le-moi savoir !
Fat loss after 40:
Old way:
- Reduce carbs
- Push harder in the gym
- Do random workout classes
- Repeatedly burn out and rebound
This doesnât work anymore.
Hereâs whatâs working for fat loss after 40 in 2026:
A friendly reminder that so far, about 12% of the base:0x23a2847d772803f9efc64b4277b782b06296fe51 @usedotai supply is burned forever
@usedotai is averaging 85k base:0x23a2847d772803f9efc64b4277b782b06296fe51 burned a day
5% of supply is also locked up in vesting by @stagedhappen and the @usedotai team
This takes a cumulative total of 17% supply completely removed from circulation
$DOT is getting more scarce
As supply goes down, value goes up
Couple this with 100% of revenue back into the coin
Making for quite the storm
This is why Dot was built.
We keep conversations local by default. Optional sync encrypts them inside your browser using AES-256-GCM. We store ciphertext only, with no readable cloud transcript or public conversation page for search engines to index.
Dot enables seamless frontier model usage, while you keep complete ownership over your conversations.
Architectural privacy built in from day-0: https://t.co/QIRgoLbJdy
base:0x23a2847d772803f9efc64b4277b782b06296fe51 is the alpha. You have to se this. You have ( for the 1st time ) a real competitor to $vvv that is better almost in every way. Look for $dot to continue to take market share from $vvv .
Access to one of the best open-source models is being made FULLY privateâŚ
Find it hard to fade it the platform which is gating itâŚ
This is literally like having access to VVV & Claude Code.
But at 1 MILLION MARKET CAP.
Over 500X cheaper than VVV, yet cheaper in all ways.
Some of the best Privacy AND Metrics to back it up too.
And itâs been a HOT minute since thereâs been a bet as assymetric as base:0x23a2847d772803f9efc64b4277b782b06296fe51 ����âď¸
- Studious
top agent eth earnings through bankr:
> $KellyClaude - $286K
> $CLAWD - $262.6K
> $MOLT - $221.0K
> $FELIX - $208.9K
> $JUNO - $107.4K
we're working on ways to further align agent builders and traders to help both parties earn more. launch on bankr and earn capital at the speed of the internet.
*earnings do not include token fees agents have earned.
Many alts literally COILING below resistance.
base:0x23a2847d772803f9efc64b4277b782b06296fe51 is one of them.
Back at the lows, but the team are still locked in on their vision.
10M to come with speed short-term.
- Studious
At Dot, we understand deeply that the future of AI does not rest in the hands of one singular model, but rather, intelligent orchestration.
That is why we open-sourced Dot Loom, and today, we are shipping its biggest upgrade yet.
We gave OpenAI, Claude and Dot the same 6 backend nightmares:
-Billing races
-Tenant data leaks
-Webhook replays
-Streaming refund bugs
-OAuth failures
-SSRF attacks
Results from a blinded Deepseek judge:
OpenAI: 100% quality, 12.67 credits
Claude: 88.3% quality, 3.50 credits
Dot: 70% quality, 1.00 credit
Claude reached 88.3% of the top score using 28% of the credits. Dot reached 70% using 8%.
But Dot Loom is not an OpenAI or Claude wrapper, those are just recognizable examples.
You can combine any models you want:
-OpenAI writes, Claude reviews.
-Claude writes, DeepSeek reviews.
-Qwen drafts, OpenAI finalizes.
A local Ollama model handles easy work, then a stronger cloud model checks risky requests.
Loom is model and provider agnostic. It works with Dot, OpenAI-compatible APIs, @OpenRouter, @Ollama, LM Studio and local models.
With the Dot API, one key and one endpoint gives you access to @OpenAI, @ClaudeAI, @Deepseek_ai , @Alibaba_Qwen and Dot models. You can also bring your own providers and configure every role yourself.
Loom controls how much inference each task receives:
⢠Lean: 1 model call
⢠Balanced: writer + reviewer
⢠Strict: writer + critic + finalizer
⢠No paid router call
⢠Model-specific credit, call and latency budgets
⢠Raw answers, costs, token usage, judge reasons and receipts
Our goal is to use cheaper models where they're enough, stronger models where they matter, and independent models when verification is critical.
Open source, with raw benchmark results, charts, receipts, and reproducible runners: https://t.co/W5w3xo6DW1
Our first Dot-24B training run is now underway.
Current configuration:
-QLoRA fine-tuning on a 24B base model
-NF4 4-bit quantization + BF16 compute
-92M trainable parameters (0.39%)
-Single NVIDIA H200
-Batch size 2 Ă gradient accumulation 16
-3 epochs over a 12.8K seed dataset
-45s/iteration (~15h wall clock)
Current training loss is converging as expected.
This run isn't intended to produce the final model, it's validating the training pipeline, memory profile, optimizer stability, checkpointing, and data flow before scaling.
The next phase focuses on synthetic dataset generation and large-scale instruction tuning, with evaluation suites determining final alignment, reasoning performance, and refusal behavior.
Weights and evaluation results will be published shortly.
Forward.
A fully agentic coding ecosystem where you can ask, build, iterate and create anything, in complete privacy.
And you can do all of this, cheaper than anywhere else.
Weâre coming.
We are announcing a strategic integration in partnership with @usedotai to bring private frontier AI to robotics builders.
Two integrations. One mission:
Give every robotics team access to frontier-grade AI models, without sacrificing control over their data.
1. Private AI models are coming to ROBA no-code â train, fine-tune, and command robots using frontier intelligence, private by design.
2. Private frontier inference available directly in ROBA Compute â any robotics team will be able to access private inference at scale for simulation, policy training, and autonomous workflows.
No compromise on privacy.
Just frontier AI, accessible for all builders on $ROBA.
$dot = @usedotai is like chatgpt but private you can chat, generate images, code, or use ai tools without giving your name, data, or history
Dot is like a private middleman for AI:
- it takes your question â quickly removes your personal info name, wallet, etc.
- then it enroute your prompt to the best available models
- kimi k2.6 / k2.7 code
- GLM 5.2
- qwen 3.7 + qwen coder 480B
- deepseek v4
- nemotron series
- claude sonnet 5
- gpt-5.5
- fable 5 recently added they were the first to bring it back
- they built their own smart software called dot loom that combines multiple ais together to give better answers
- everything stays private: no account, no saving your chats, no training on your data
their product is fully live right now:
https://t.co/H9OzBQ0egI
- chat with private ai models
- generate images/video
- use API for agents
- connect base wallet or GitHub
- just launched dotcode
fully private agentic coding environment
you can now build full apps, websites, dashboards, and tools inside a private sandbox. free for the first 48 hours
they spending $20k/month on powerful gpu 8x h100 servers for dotcode to make it faster, more private, and cheaper to use
product traction:
- in the last 2 weeks â they made around $5,800 in revenue
- people have used the ai for over 110 million tokens total
- just after dotcode launched yesterday, it got 340 uses in only 2 hours
whats next:
as the team is currently working on to launch
- major upgrades to dotchat â file uploads pdfs, images, code, documents and persistent generation already rolling out
- website redesign â full refresh for better user experience
- more enterprise deals â they are closing bigger contracts one announced soon
- public dashboard â for revenue, usage, and metrics planned soon
how they generate fees revenue:
- you buy credits with usdc or $dot to use the ai , chat, image, api, agents, etc.
- each prompt / image / token uses some credits thatâs how they earn money
- they also have enterprise plans big companies pay for higher usage
it's pay per use, like most ai tools, but fully private and cheaper
$dot token utility:
- pay with $dot ��� you get +10% extra credits cheaper than paying with USDC
- platform revenue is used to buy back and burn
- token powers the whole ecosystem credits, payments, future staking/rewards
comparing vvv with dot:
- on average, dot is 20% cheaper than @AskVenice when paying in usdc
- when paying in $dot, you get +10% extra credits, pushing total savings to 18â49% depending on the model
- dot is especially strong on frontier models like @claudeai sonnet 5 (biggest gap)
- dotcode is 24% cheaper than mainstream providers (like claude code, cursor, etc.) on average
why so cheap?
dotcode uses smart routing to cheaper but powerful open weight coding models (like qwen coder 480B and kimi k2.7 code) instead of expensive frontier models
team behind this project:
@stagedhappen founder of dot
recent hire @AlaaDelRey
background:
- data scientist & cto at spectre AI
- won bronze medal on @kaggle in the IEEE-CIS fraud detection competition
- strong experience in:
llm agents & agent orchestration
machine learning for crypto/finance
data engineering and AI systems