Consciousness Architect š Trim tabs for cooperative abundanceš¦
Joined June 2020
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Alpie Core is a 32B reasoning model trained and run natively at 4-bit, so it keeps strong reported scores on math (GSM8K) and coding (SWE-Bench) while needing far less memory than typical full-size models. They're also showing a 9B version running locally on a phone.
The differentiation is efficiency and real deployability, not just raw model size.
@PIEby169Pi @PIEby169Pi solana:aqQRs3UJmHs7ktoLo46HZAzvG9P3oCoZ41nENqFbory
Last time $PIE had a 3D bulldiv like this it 20-X'd in a matter of weeks
@PIEby169Pi
Nobody say anythingš«¢
A 9B model. 4-bit. 82.54% on MMLU-Pro. Running on an iPhone. Alpie Seed is showing that strong reasoning doesn't have to live in the cloud. Built by @169pi. $PIE is being built as the access and coordination layer that powers the ecosystem around it. The intelligence is already here. The infrastructure is coming.
@169Pi_ai @PIEby169Pi
The real risk isnāt that AI fails. Itās that the current buildout is financing yesterdayās model of intelligence.
**Alpie** is proving you donāt need trillion-dollar infrastructure to get frontier reasoning. While the industry takes on massive debt to fund ever-larger clusters and circular chip deals, Alpie Core is a 32B model trained and served entirely at 4-bit. Trained on just 8 GPUs. ~75% less memory. Roughly 10x cheaper to run than GPT-4 class models. Competitive or better on reasoning, math, and coding benchmarks. Deployable from the cloud all the way down to the edge.
Less capital intensity. Faster path to real unit economics. No dependency on endless debt-funded capacity.
**$PIE is the token for the Alpie ecosystem.** Utility is still planned, but the direction is clear: an access and coordination layer built around efficient, deployable AI instead of hyperscale leverage.
Efficiency is the new scale.
@169Pi_ai @PIEby169Pi
šØ The AI BUBBLE is starting to look like a MUCH bigger problem than overpriced tech stocks
More than $2 TRILLION was on track to be wiped off the Nasdaq 100 in October, and now Wall Street is getting nervous about something far more dangerous: DEBT.
Blackstone expects Anthropic to receive a JUNK credit rating after its IPO, according to the FT, even as the company plans more than $800 BILLION in computing investments through 2045.
Amazon is burning through cash. Alphabet just lost roughly $500 billion in market value in ONE DAY. And CoreWeave's borrowing costs have reached levels that would make most companies sweat.
Here's where things get crazy.
AI companies are borrowing BILLIONS to buy chips from suppliers who are increasingly helping finance the very customers buying those chips.
That's a LOT of money moving around the same circle.
And the entire industry is just betting that future AI revenues will eventually justify the enormous costs of building all this infrastructure.
Nobody is even questioning whether AI is actually useful.
They're rather questioning whether the spent TRILLIONS to build it will ever make returns.
And if the debt markets lose confidence before those profits arrive, this could get ugly VERY quickly.
Source: MarketScreener, Investing[dot]com, Bloomberg / Writer: Oliver
This is the market Alpie and solana:aqQRs3UJmHs7ktoLo46HZAzvG9P3oCoZ41nENqFbory exist for.
Not for the user asking ChatGPT for recipes.
For the business that canāt let its data leave the building.
For the team or institution that needs AI on their own terms.
Local inference isnāt a bug. Itās the product.
@169Pi_ai @PIEby169Pi $PIE
Itās not that every person necessarily wants to run their own local systems; itās that some nontrivial percentage want/need to do that.
Businesses and individuals protective of their data privacy, or wanting to analyze/perform things that centralized providers might block from being analyzed/performed.
Obviously both datacenters and local setups are useful, depending on the context.
Efficiency is the new frontier.
Alpie Seed 9B (from @169Pi_ai) is out-deciding larger models in real time on the same Pong task ā lower latency, higher throughput.
This is what practical, deployable AI looks like: not just bigger parameters, but models that actually run fast enough for the real world.
Indian lab shipping. solana:aqQRs3UJmHs7ktoLo46HZAzvG9P3oCoZ41nENqFbory
What? No way š±
An AI Lab out of India is silently cooking models that beat top frontier models!
Actual run: alpie-pong.vercel.app
The oldest power move isnāt force. It is controlling what people are allowed to think with, printing press, broadcast tower, algorithm. This is happening again with AI accessibility. What changes the game isnāt a better argument. Itās intelligence you can hold and own. Alpie is a deployable reasoning model: open weights, full access, no permission required to run. The agentic layer is being built on that foundation, in stages, in the open. $PIE is the utility and access layer to the @169Pi_ai ecosystem. What this means economically is still taking shapeāand is worth paying attention to. The answer to centralized control has never been protest. It has been self-sufficiency.
Notice how the AI narrative is increasingly built around fear?
Hacking governments, collapsing banks, breaking cryptography, threatening national security. But rarely about curing previously incurable diseases, discovering cancer treatments, or breakthroughs that could change humanity forever.
AI is capable of both, yet itās the governments who gets to decide which future we pursue. Psychologically, fear is the easiest way to make people accept control, convince society that something is dangerous enough, and theyāll willingly surrender their freedom to feel safe.
This is why open source AI, local models, and decentralized networks like Bittensor matter so much because for the first time, humanity could have access to intelligence that no government or corporation can fully control.
The greatest threat isnāt AI becoming too powerful, itās the world governments who gets to decide on what they want to use it for.
The noise is loud. The builders are quiet. While everyone's watching the meta flip, $PIE is laying down foundation ā AI infrastructure, real utility, long-term vision. Solana deserves projects that build through the cycle, not just ride it. šļøš„ #PIE #Solana #Web3
The real breakthrough isn't just running a 9B model on a phone. It's making intelligence independent of the network. When AI works the same with the internet switched off as it does when it's on, the entire relationship changes - from something you access to something you carry.
$PIE is being built as the utility and access layer for this stack - the coordination piece that lets developers, enterprises, and users participate in on-device capability without routing everything back through the cloud. This is what local AI has to look like if it's going to matter beyond demos.
A 9B AI model. Running on an iPhone 17 Pro. No cloud required.
What if your AI assistant worked just as well on a flight, in a remote location, or with your internet switched off?
We are working to make that a reality with our 9B model. Weāve successfully run it locally on the iPhone 17 Pro, recording 230.65 tokens/sec in prompt processing, 9.59 tokens/sec in generation, and 7 GB peak memory usage in our benchmark.
This is what makes local AI interesting beyond the technology itself. Developers can explore apps that work offline. Enterprises can bring AI closer to sensitive workflows. And users can access AI for coding, research, and writing without every interaction depending on a remote server.
AI that works without the internet changes where, when, and how you can use it.
We are pushing this further at @169Pi_ai. Our work on the model is ongoing, with a focus on making the model more accurate, faster, and more efficient on consumer hardware. Getting all three right on a phone is the challenge weāre working to solve.
The iPhone 17 Pro is one step. Thereās more to come.
Tomorrow, weāll share how Alpie Seed runs on other devices.
The goal is simple: make capable AI available wherever you need it, not just wherever you have a connection.
nitsuj retweeted
Pairing accessibility with impressive coding performance (61.2% on SWE-Bench) is what sets $PIE @169Pi_ai apart. And they keep perfecting their model.
A 9B model is small enough to run on normal hardware That means it can realistically run on a modern laptop FULLY OFFLINE
Compared with their earlier 32B model (which needed ~16 GB), this is a BIG drop in requirements. And Compared with the more known models that need multiple high-end GPUs or the cloud, the difference is large
Why this matters:
- Code and data stay on your machine - Works without an internet connection
- Run code intensive AI work anyway
The ticker is $PIE
A 9B model scoring 61.2 on SWE-Bench Verified is interesting.
Making that level of coding capability available to run locally is what makes it exciting.
At 169Pi, we are working towards AI that can tackle real software engineering and scientific reasoning tasks without always depending on the cloud.
Think about what that could mean for developers, enterprises working with proprietary code, researchers handling sensitive work, or anyone who wants capable AI even without an internet connection.
Less dependence on remote infrastructure. More control over where intelligence runs.
We are pushing the limits of what's possible with efficient models, and we're getting ready to show you what we've built.
Starting now, we'll be sharing something new we are building every other day. The research, the experiments, the breakthroughs, and the work behind them.
More soon.
A 9B model. Local. No cloud. 61.2 on SWE-Bench Verified. Serious coding capability now fits on your machine. This is the infrastructure shift $PIE was built for. Not hype. $PIE is the access layer for AI that runs where you need it. Early is early. š
A 9B model scoring 61.2 on SWE-Bench Verified is interesting.
Making that level of coding capability available to run locally is what makes it exciting.
At 169Pi, we are working towards AI that can tackle real software engineering and scientific reasoning tasks without always depending on the cloud.
Think about what that could mean for developers, enterprises working with proprietary code, researchers handling sensitive work, or anyone who wants capable AI even without an internet connection.
Less dependence on remote infrastructure. More control over where intelligence runs.
We are pushing the limits of what's possible with efficient models, and we're getting ready to show you what we've built.
Starting now, we'll be sharing something new we are building every other day. The research, the experiments, the breakthroughs, and the work behind them.
More soon.
Easy to dismiss a chart. Harder to dismiss what I use daily. Alpie is live. The model is real. The ecosystem is moving. $PIE isn't asking you to believe in a promise ā it's asking you to pay attention before everyone else does. š
While AI grows powerful enough to outpace human discovery, the real risk is losing the curiosity and expertise that make progress meaningful.
$TIG flips that script: an open protocol that coordinates global intelligence, rewards anyone who advances algorithms for real challenges in AI, science, climate, and more, and keeps innovation decentralized instead of locked away.
This is how society stays in the gameānot as passive observers of the tsunami, but as active builders of what comes next. The future of useful discovery stays open. #DeSci $TIG
Fields Medalist Timothy Gowers raises a troubling possibility: AI could become so powerful at mathematics that future generations may lose the motivation to study the subject deeply enough to understand its discoveries.
The paradox is striking. Machines might eventually solve problems far beyond human capabilities, while fewer mathematicians possess the expertise needed to interpret their results.
For Gowers, the deeper concern extends beyond the future of mathematical careers. It is about preserving the curiosity, intellectual discipline, and satisfaction of discovery that have sustained mathematics for centuries.
He also envisions a possible transformation of the mathematicianās role, from discovering new theorems to interpreting, connecting, and explaining mathematical knowledge generated by AI.
Reflecting on the approaching social consequences, Gowers offers a vivid analogy:
āWeāre still on the beach, we can see the tsunami, but it hasnāt quite reached us yet.ā
Importantly, he is not calling for mathematics departments to close or for universities to stop admitting PhD students. His remarks are cautious predictions about a possible future, rather than descriptions of changes that have already taken place.
What if the next wave in crypto isn't speculation, but actual access?
Access to AI infrastructure. Access to model tiers and capacity. Access to governance over how models evolve.
That's what $PIE as the utility token for the Alpie ecosystem could represent ā not just 'crypto meets AI' as a slogan, but as a working coordination layer between holders and a live, deployable AI stack.
With Core already live, open-source, and running on consumer hardware, and the Alpie app now on iOS and Android, the infrastructure layer is real.
With a new model launch on the horizon, the utility picture feels closer than ever. What will holding $PIE actually unlock, and what is the potential here? š
@PIEby169Pi @169Pi_ai
š¤ Made with AI
Itās here. Alpie is now on iOS and Android.
The way we work with AI is changing. Weāre building Alpie to make that experience more useful, more collaborative, and more accessible, wherever you are.
Now, you can take Alpie with you.
Your ideas donāt have to wait until youāre back at your desk.
Download #Alpie and experience it for yourself.
iOS: apps.apple.com/app/alpie/id6ā¦
Android: play.google.com/store/apps/dā¦
Weād love to hear your thoughts. Your feedback will help shape what comes next.
Fields Medalist: OpenAI āannihilated my field.ā He cried.
Closed AI labs donāt just solve problems ā they collapse the human discovery process that creates the next ones.
$TIG is the open alternative.
Decentralized market for algorithms. Rewards innovators + benchmarkers. Licensing fees buy the token. Progress stays open, value accrues to the network.
Algorithms run the world. Donāt let them stay locked up.
$TIG
Fields medallist Hugo Duminil-Copin was deeply shaken by OpenAIās release of more than 700 AI-generated mathematical manuscripts, including work on 16 questions directly relevant to his research.
āOn Tuesday night, I cried, and it woke up my daughterā
āThey have annihilated my field of research.ā
lemonde.fr/sciences/article/ā¦
nitsuj retweeted
Every seed carries its DNA long before the world sees what it becomes. $PIE's DNA? Community. Utility. Liquidity. Narrative. The Alpie Seed launch isn't the beginning of something new ā it's the moment the blueprint finally starts breathing. What's coded into $PIE has always been there. Now watch it grow. š±
Every seed carries its DNA long before the world sees what it becomes. $PIE's DNA? Community. Utility. Liquidity. Narrative. The Alpie Seed launch isn't the beginning of something new ā it's the moment the blueprint finally starts breathing. What's coded into $PIE has always been there. Now watch it grow. š±
Try Alpie on your mobile device. xitter.gq/169pi_ai/status/210893ā¦
Itās here. Alpie is now on iOS and Android.
The way we work with AI is changing. Weāre building Alpie to make that experience more useful, more collaborative, and more accessible, wherever you are.
Now, you can take Alpie with you.
Your ideas donāt have to wait until youāre back at your desk.
Download #Alpie and experience it for yourself.
iOS: apps.apple.com/app/alpie/id6ā¦
Android: play.google.com/store/apps/dā¦
Weād love to hear your thoughts. Your feedback will help shape what comes next.
nitsuj retweeted
Itās here. Alpie is now on iOS and Android.
The way we work with AI is changing. Weāre building Alpie to make that experience more useful, more collaborative, and more accessible, wherever you are.
Now, you can take Alpie with you.
Your ideas donāt have to wait until youāre back at your desk.
Download #Alpie and experience it for yourself.
iOS: apps.apple.com/app/alpie/id6ā¦
Android: play.google.com/store/apps/dā¦
Weād love to hear your thoughts. Your feedback will help shape what comes next.
nitsuj retweeted
One parcel of my identity is a food-growing gardener. I read @BrianRoemmele blog earlier this week and thought to share the newsā¦
Plants bred for yield, speed, and size are delivering up to 50% less of several key nutrients than they did a generation ago.
There is more output, yet less nourishment. The effort looks the same on the surface. While, these high yield crops grew larger and faster - they stopped building the root that actually struggles and searches for its nourishment needs.
I was immediately struck by the parallel between plantsā roots that have to struggle, do contain higher nutritional value and our human struggles that seem to be a gift (in a way) to help us grow into a quality being. š
So, hereās a question in a question ā
āHow often are we productive yet not nourished? Busy yet not fed? Moving through the days doing real, meaningful things - and arriving somehow hollow?
š± The Enneagram points to something quiet here. Each type has its own way of optimizing for output over depth. Doing over receiving. Producing over resting inside what was made.
The plant that never has to struggle stops building the root that searches.
I think we do too. Comfort over uncertainty.
For instance, I can move through an entire day doing meaningful things and still arrive at the end of it strangely empty. Not because nothing happened. Because I moved through it instead of into it.
The root has to go somewhere my schedule doesn't reach.
I would love your thoughts on this!
š±
Source Citation:
thegrocer.co.uk/news/crops-hā¦
Research from Hollow Harvest, Deep Science Ventures, as reported by The Grocer, October 2026 - supported by Davis et al., Journal of the American College of Nutrition, 2004, and the Broadbalk wheat archive at Rothamsted Research.
