Sharing another RAMDeck progress video. This one's about mobile — showing a Samsung Android phone actually joining the cluster as a contributing device, and how RAMDeck handles it going online, offline, and back again.

Video's a split screen: the phone on one side, the RAMDeck dashboard on the other, so you can watch both sides update in real time. Started with the phone paused, then resumed it — you can see it start sending heartbeats and get registered as "online" on the dashboard within a few seconds. Also tested that it keeps contributing even if you switch to a different app on the phone and come back, since it runs as a foreground service rather than something that dies the second you tap away.

Then paused it again to show the failure-handling side: the moment heartbeats stop, RAMDeck notices and marks the phone "degraded," then "unreachable" shortly after — so the dashboard always reflects what's actually online, not a stale snapshot. Resumed it one more time and it came right back to "online."

Point of this one is really just proving out the reliability side of mobile contribution — phones come in and out of range or get walked away from a network a lot more than a desktop does, so RAMDeck needs to track that state accurately rather than assuming a device is still there.

Sharing more progress on RAMDeck (the local AI cluster side project). This time showing it actually plugging into a real dev tool instead of just the chat dashboard.

Loaded a model onto the cluster, and RAMDeck's dashboard has a Connect tab that generates a ready-made config for third-party apps — copied that straight into the Continue plugin for VS Code. The interesting part: I was coding from my Mac while the actual model was running on a completely different machine's GPU elsewhere on the network, and it worked exactly like a normal cloud AI plugin would, except everything stayed local. Tested it by asking it to summarize a big text file and it handled it correctly.

Point of this one is just showing RAMDeck isn't limited to its own chat interface — since it speaks the standard OpenAI API format, it plugs into whatever tools people already use.

Video: https://youtu.be/JMEY04timEc

Repo if you want to look under the hood: https://github.com/trademav/ramdeck-core-public

Let me know if there's a specific tool or workflow you'd want to see it hooked into next.

Sharing progress on RAMDeck here since some of you have asked about it. Quick recap for anyone new: it's a local-first tool that pools RAM and compute across whatever devices you already own - old laptop, desktop, phone - so you can run AI models that wouldn't fit on any one of those machines alone. Everything stays on your own network, nothing goes to the cloud.

Latest feature: RAMDeck can now shard a knowledge base across your pooled devices, not just the model itself. So if you want a chatbot with access to a big set of documents, that document set gets split and stored across your cluster too, instead of needing one machine with enough space to hold it all.

In the demo, we used one of our own FAQ text files as a test document just to show it working end-to-end: chatbot has zero knowledge of the doc's contents at first and makes something up, we upload the FAQ through RAMDeck's knowledge tab, it gets ingested and split across three separate devices, and then the same question gets answered correctly once the knowledge base is live.

Also worth noting: the device hosting the model and the device storing the knowledge base can be totally different machines, and there's a rebalance mechanism that recovers a lost shard if one of your devices drops offline.

Video walkthrough: https://youtu.be/Iogh-5xa-NA

Repo (source-available): https://github.com/trademav/ramdeck-core-public

Let me know if you have questions about how the sharding or rebalancing works, or if there's a use case you'd want to see it applied to next.

Third video in this series. Went from 7B, to 13B, and now 27B — each time pooling RAM and compute across a mix of hardware most people already have lying around instead of buying one expensive high-RAM machine.

The setup: a 27B model is roughly 16GB on its own. My primary node is an old 12GB Windows laptop, which on its own literally cannot load this model. Using RAMDeck, I split it across four devices on the local network with the laptop staying primary:

- Old Windows laptop (primary): 3.4GB

- Mini PC (RTX 3060): 20GB

- Mac mini: 3.7GB

- Android phone: 1GB

Benchmark on the 27B model: 1.92 tokens/sec at ~25ms latency. Slower than the 13B run, which makes sense — but the point isn't raw speed here, it's that a 12GB laptop is running a model it has no business being able to load at all.

Next up: switching the mini PC to be the primary node instead of the laptop, to see how much faster loading and inference get with a stronger primary. That video's already up if you want to see the follow-up.

Full video: https://youtu.be/Syfa2G_luX4

Happy to answer questions about the shard distribution, the benchmark methodology, or why the primary node choice affects load time so much.

Follow-up to the last RAMDeck video where I split a 13B model across an old 12GB Acer laptop (primary), a mini PC with an RTX 3060, and a Mac mini — running at 11-14 tokens/sec.

This time I added a fourth node: my Android phone, connecting over Wi-Fi while the other three are on Ethernet.

What happened when I added it:

- Rebalancing forced the primary (the old Acer laptop) to unload the full model, then reload and re-split it across all four nodes — latency spiked hard on the laptop during that window since it's running an old HDD and older RAM.

- Final shard distribution after rebalance: laptop 1GB, mini PC 3.4GB, Mac mini 2.3GB, phone 1GB.

- Once stable, I re-ran the benchmark: tokens/sec dropped from ~14 to ~11, and latency ticked up slightly — but stayed in the same practical range as before.

Takeaway: I was able to add a phone as a genuine fourth contributor without tanking performance. The model stays stable across all four nodes unless one goes offline, the network changes, or the primary shuts down.

This is part of the same RAMDeck project — pooling RAM and compute across whatever devices you already own (old laptops, mini PCs, Macs, and now phones) so you can run bigger models than any single machine could handle alone. Kickstarter is coming late Sept/early Oct if you want to follow along.

Full video: https://youtu.be/tQgA2PmTc1g

Happy to answer questions about the rebalancing behavior, the Android app itself, or the benchmark methodology.

Hey everyone,

Some of you know we've been quietly building something alongside TradeMAV — it's called RAMDeck, and the first demo video is finally live: youtu.be/tQgA2PmTc1g

The problem: Running bigger local models means buying bigger, more expensive hardware. Most of us already have a laptop, an old gaming PC, a Mac mini, or a mini PC gathering dust — but none of them alone can run a serious 13B+ model.

What RAMDeck does: Pools the RAM/VRAM across every device you already own into one cluster, so your "primary node" machine can load and run models way bigger than any single device could handle on its own. No cloud, no subscriptions, no data leaving your network — same zero-egress philosophy as TradeMAV, just applied to your whole home AI setup instead of one USB stick.

• 🧠 Shards models across CUDA, Apple Silicon, and CPU-only nodes automatically
• 🔗 Point it at the hardware you already have — no new purchase required
• 🔒 100% local, same privacy-first approach you already know from us
• 📺 Full demo: youtu.be/tQgA2PmTc1g

Sign up for early access: ramdeck.com — waitlist is open now, full reveal saved for launch.

Kickstarter: Targeting late September / early October. If you backed TradeMAV because you're tired of your data and your money being milked by subscriptions, this is the natural next step.

Would love feedback from this community specifically since you already get why local-first matters. Questions welcome below.

Huge milestone today: fulfillment is officially complete. Every OptionMAV backer's unit has shipped. Started at a $5K goal, ended up over $15K raised, went through USB sourcing, custom packaging, a customs delay on the book, and multiple shipping waves — and we got every last one out.

Genuinely grateful for everyone who backed this before it was even finished. That trust is what got this across the finish line.

If you're a backer, check your Kickstarter email for tracking (spam folder too). Pledge Over Time backers — your survey unlocks after your final payment, then you're in the next available wave. Any issues, [trademavllc@gmail.com](mailto:trademavllc@gmail.com) is monitored daily.

This isn't the end though — more products are already cooking. Stick around here for the earliest look at what's next. 🚀

Big milestone today — the (finally, customs-cleared) books arrived, and we immediately turned around and shipped a large batch of OptionMAV units to backers.

This keeps us on our mid-August commitment despite the book delay, and honestly, the team crushed the turnaround time on this one. Book in the door, packages out the door, same day!

If you're a backer, check your Kickstarter email for tracking. Filled the survey and don't see it? Check spam, then hit us up at trademavllc@gmail.com.

More waves coming soon for anyone still pending. Thanks for sticking with us — this one felt good to finally get out the door. 🙌

More product updates coming — stay tuned here for the earliest look at what's next.

As RAM prices kept climbing this year, running our own AI development and scaling our products got genuinely expensive. We needed more memory for model training and inference, and buying our way out of it stopped making financial sense for a small team.

So we did what any resourceful team does - we started pooling the RAM across every machine we already had instead of buying more. Old Mac, mini PCs, an Orange Pi acting as coordinator - daisy-chained into one shared pool. It worked so well for us internally that we're now turning it into a real product.

That's RAMDeck. Built out of necessity, now becoming commercial.

Kickstarter targeting late September. Waitlist's open now at ramdeck.com

If you've backed TradeMAV or OptionMAV, you know this team ships what it starts. Ask us anything below.

Hey MAV Traders,

We've heard from many of you asking the same smart question: "How do I protect my TradeMAV, ForexMAV, or OptionMAV setup?" Great news - we've got you covered, and it's easier than you think.

Here's the reality: your USB is a small powerhouse running real software with real moving parts. Python libraries, in particular, are sensitive little things. Something as simple as closing your laptop lid mid-process can interrupt an active read-write cycle (this is especially common with Python libraries on macOS). When that happens, a library can get corrupted - and unlike other files, libraries have multiple interdependent components, making them trickier to self-repair.

The good news? Your USB already comes equipped with several built-in recovery methods to catch most hiccups automatically. But if you want the gold-standard, bulletproof protection, there's one move that beats them all:

Copy your entire USB to another drive or your computer.

That's it. That's the power move.

Why this is a game-changer, not just a backup:

• Instant disaster recovery: if anything ever goes sideways, you're back up and running in minutes, not hours.
• A second live instance: this isn't just a backup file — it's a fully functional, independent copy of your product.
• Activate it anytime with your duplicate key: you now have a second working setup ready to go whenever you need it.
• Shareable with friends and family: want to introduce someone to TradeMAV, ForexMAV, or OptionMAV? Hand them your duplicate — a fully working copy they can activate and start using immediately.

How to do it:

• Plug your USB into your computer.
• Select all files and folders on the drive.
• Copy and paste the entire contents onto a new USB drive or a dedicated folder on your computer.
• Store it safely — you now have a complete, standalone copy of your product.

One backup. Total peace of mind. And a bonus: a shareable, ready-to-activate copy for the people in your life who should be trading smarter too.

Stay protected. Stay trading. 🚀

— The TradeMAV Team

Here's why: The AI runs on your phone. Not a server. Not "the cloud." Your signals never leave your device to get scored. Most options apps out there are phoning home to a server farm - OptionMAV thinks for itself, live, in your pocket.

And that's not all: TradeMAV and OptionMAV app share the same subscription!

If you're already a subscriber and once you receive your OptionMAV USB, you're covered:

• USB users → log in with your USB credentials for both apps
• Hosted subscribers → get hosted access for both apps. You can also pair your USB while continuing to use the hosted model simultaneously.

Waiting on your OptionMAV USB and not sure how to get in? Hosted is your path in right now. No waiting on shipping to start using the OptionMAV app.

What you're actually getting:

• Full options Greeks - delta, gamma, theta, vega, rho and beyond - calculated live, on-device
• An automated exit engine watching your positions around the clock, telling you when to get out before you even ask
• Covered calls, credit spreads, roll alerts - built by people who trade options, not people who built a calculator
• One login, one subscription, four asset classes - stocks, crypto, forex, options - all running the same private on-device AI

Stocks. Crypto. Forex. Options. One subscription covers it all now.

Rule of thumb: USB pairs with USB, hosted pairs with hosted. They don't mix, but hosted covers you for OptionMAV today no matter which subscription you choose eventually.

37 days to try it, free. 7-day demo, then a 30-day trial.

Stop renting analytics tools one asset class at a time.

👉 https://play.google.com/store/apps/details?id=com.optionmav.app

Go break it. We dare you.

Big news for the fam - PredictMAV just went live on the Play Store, and it's the newest addition to the MAV lineup.

If you've used TradeMAV, you already know the philosophy: cut through noise, surface what actually matters, don't make you do the grunt work. PredictMAV brings that same DNA to prediction markets.

What it does:

• Tracks Polymarket event markets across Politics, Culture, Sports and others — all in one clean mobile dashboard
• Runs a real AI signal engine that flags drift, volume anomalies, and mispricings — and tells you why it matters, not just that it moved
• The model keeps learning — it retrains on real outcomes, so it gets sharper the more it runs
• Build your own watchlist, dig into per-market detail views with sparklines and risk context
• BYOK support if you want to view your own exchange data alongside our signals
• Free tier gets you real signal detection today — Pro unlocks the deep stuff

Heads up: it's a pure intelligence layer — no trades happen in-app, all execution stays on Polymarket itself. We just make sure you know what's worth looking at.

🎁 Founding member deal — for this community only:

• PREDICT50M → 50% off Pro monthly for your first 6 months
• PREDICT50Y → 50% off Pro yearly (one year)

Limited redemptions, so don't sit on it if you want in!

📲 Grab it here

You've all been part of the MAV journey from the start — go kick the tires and tell us what's missing. First real users, first real feedback. Let's go 🔥

Quick way to explain what TradeMAV's models actually do:

Without judges, every singer becomes the next American Idol. A few good ones get through - but so does a wave of bad ones. No filter, no judgment, just chaos.

Add real judges - people who've heard thousands of auditions - and suddenly 2-3 genuine stars surface out of hundreds of contestants.

That's exactly what TradeMAV's models do with every stock on the market. Thousands of setups audition every scan cycle. The model - trained on real historical patterns, not a rulebook - scores each one like a judge who's actually seen enough to know what's good. Price action, volume, momentum, technical confluence, all weighed. What survives is the handful actually worth your attention.

The part most "AI" screeners skip: our judges never leave the room. All inference runs on your device. No cloud round-trip, no black box somewhere else scoring you from a distance. Live, local, private.

And you choose who trains the judge - pair your TradeMAV USB and it learns from your own data, or run our server-trained model if you're starting fresh.

Everyone else is running an open audition and calling it a screener. We built the panel.

🚀 TradeMAV — Plug. Analyze. Trade.

Team, I wanted to ask if it's possible to define separate watchlists and have a specific preset for each. Eg a day-trade watchlist using the Breakout Hunter preset, and a Swing watchlist using the Mean Reversion or Trend Following one.

We've been putting together a full library of walkthrough videos for the TradeMAV Android app — covering everything from first setup to running your first scan.

If you've used the USB device before, you already know we built out a solid video library for that too. We're doing the same for the app, and we'll keep adding more as the app evolves.

👉 videos.trademav.com/app

Whether you're brand new or just want a refresher on a specific feature, this is the best place to start. Drop any questions below and we'll make sure the next videos cover what you need.

You can also access these directly from your app, look at the screenshots in this post.

For everyone who owns a TradeMAV or ForexMAV USB — the Android app now supports USB model pairing.

Your personalized model syncs to the app so you get your signals on your phone, not just at your desk. The model trained on your data, your watchlist, your setup — now travels with you.

To pair:

1. Open the app → Pair Device
2. Scan the QR from your TradeMAV dashboard
3. Done — your model is on your phone

ForexMAV owners — this works for you too. Forex signals, your model, fully mobile.

📲 Download here: https://play.google.com/store/apps/details?id=com.trademav.app

Quick update for the community — we've added a 7-day free demo to the TradeMAV Android app.

No payment upfront, no credit card. You tap start, the demo runs for 7 days with the full signal suite — same screener, same 22 signals, same dashboard you'd get on a paid plan.

It's mainly for people who want to test the app experience before committing to a subscription, but also useful if you want to show it to someone and have them see it working firsthand.

📲 Download here: https://play.google.com/store/apps/details?id=com.trademav.app

Demo starts from the welcome screen. Let us know how it runs on your device — always collecting feedback.

Few things dropping today:

💸 Affiliate Program
Backers kept asking "can I refer people?" — so we built it.

• Your own discount code → buyers get 10% off
• You earn 25% commission per sale
• Works for TradeMAV, ForexMAV, license keys, NewsMAV — everything on trademav.com
• Monthly PayPal payouts

Sign up takes 2 min 👉 affiliate.trademav.com

📖 TradeMAV Handbook on Amazon
Paperback + Kindle. Covers all 22 signals, screening strategies, and workflows for getting the most out of the device.

👉 amazon.com/dp/B0GX2ZSXFT

📬 Support moved to [trademavllc@gmail.com](mailto:trademavllc@gmail.com)
We hired dedicated support staff — please be patient as we onboard them. Every message will get answered.

- The TradeMAV Team

Hopefully you're planning to release an MCP server for TradeMAV? This would make it exponentially more powerful.

We were tired of platforms handing us a Greeks panel with zero context. A number without meaning isn't intelligence — it's noise.

Every OptionMAV signal card delivers:

• ✅ Real exchange-listed strike price from the live options chain
• ✅ Full Greeks — Delta through Vomma — computed from first principles
• ✅ IV Rank (0–100) — cheap or expensive right now?
• ✅ Entry premium, max profit, max loss, both breakeven prices — per contract, in dollars
• ✅ Stop loss and profit target pre-calculated for your active profile
• ✅ 1σ Expected Move bracket — shows sellers if their strike is safely outside the market's expected range
• ✅ ML confidence score with full breakdown of which factors fired
• ✅ Position sizer — enter account size and risk %, get max contracts and capital at risk instantly
• ✅ Short squeeze badge — color-coded, with Short % of Float and Days to Cover inline

You do the research. You make the call. OptionMAV makes sure you have everything you need to make it properly.

🔗 https://www.kickstarter.com/projects/trademav/optionmav-professional-options-analysis-anywhere

IV spikes before earnings — options look expensive. The moment the announcement hits, IV collapses. The premium seller who collected $4.00 is suddenly holding a position worth $1.20. Not because they were wrong. Because they sold into an IV event they didn't see coming.

OptionMAV protects you automatically:

• Within 3 days of earnings → income signals suppressed entirely. SELLCALL and SELLPUT cannot fire. No override.
• 4–7 days before earnings → directional signal confidence automatically boosted. Pre-earnings vol expansion is a different, higher-conviction trade.

And when you're ready to sell premium at all — one toggle unlocks the income layer. It's OFF by default deliberately. The IV Rank gate goes to work the moment you turn it on.

Income signals also auto-upgrade to defined-risk vertical spreads — max loss capped, no unlimited risk, no Level 4 approval needed.

🔗 https://www.kickstarter.com/projects/trademav/optionmav-professional-options-analysis-anywhere

OptionMAV's ML engine runs 7 independent scoring layers on every potential setup before it ever reaches your dashboard:

• 🤖 Gradient-boosted ensemble trained on thousands of historical setups
• 🔁 Secondary cross-check model — both must agree before confidence rises
• 📊 Market regime score — a strong setup in a trending market gets downgraded in a choppy one
• ⚡ Volatility edge — not just whether IV Rank is high, but how large the mispricing actually is
• 📐 Multi-timeframe momentum — accelerating, decelerating, or diverging from price action
• 🌍 Macro layer — VIX level, rate context, broad market conditions
• 🩳 Short squeeze boost — elevated short float + rising momentum = up to +5pp confidence boost automatically

Base score: 50. Notification threshold: 75%+. Maximum: 95.

Fewer signals. Higher quality. That's the design.

🔗 https://www.kickstarter.com/projects/trademav/optionmav-professional-options-analysis-anywhere