Growth & Marketing. Building distribution, activating ecosystems and driving growth beyond headcount. Stablecoins & RWAs @realfi_co.
Do ut des
Joined January 2010
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AI promises superabundance. But for whom? The singularity, the superposition and the swarm. A fight over who owns the intelligence we’ll all depend on. The Event Horizon. Act III of Survival of the Sovereign.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
Worst mass breach of privacy by a company in history.
OpenAI/Anthropic: The user is banned for violating the ToS.
Also OpenAI/Anthropic: PLEASE MR. PRESIDENT BAN OPEN SOURCE AI BECAUSE IT IS SO UNSAFE AND ONLY WE CAN BE TRUSTED
Deepseek aura mogging...
Ben 🇬🇧🇺🇸🇯🇵 retweeted
Google and AI are completely different, and understanding how they work changes how you use them.
*To be specific: by “AI” here I mean Large Language Models, or LLMs. Google has technically always been AI – its PageRank algorithm, which decides which links to return to you, has always been a form of AI. And yes, Google is now augmented with LLMs. What we’re comparing in this post is traditional Google (using PageRank) and LLMs.*
Lets break down the differences in plain English & answer some of the most commonly asked questions below (so you know when to use which tool):
Q: What’s the biggest difference between Google and LLMs like ChatGPT?
Google searches. LLMs predict.
Google scans the internet and returns the most relevant websites using a ranking system.
LLMs don’t search. They learn from massive amounts of text — and then predict what word comes next based on probability.
Q: So are LLMs just looking things up?
No. They’re word generators. They learn patterns in language, and then generate text that follows those patterns.
That’s why they can sound confident — even when they’re wrong.
Many - crucially, not all!!! - models today have been augmented with the ability to pull some data from the internet and insert it into its context window (i.e. the input into the LLM, the prediction machine) which reduces the risk of “hallucination,” (i.e. making things up) but even so, the model is still a predictor. It can (and often does) still mess up EVEN with web search added.
Q: What’s the biggest tradeoff to watch out for?
Hallucinations. LLMs are generators (& not a fact checkers). So they can make things up.
That’s why tools like web-browsing and retrieval-augmented generation (RAG) are so important. They anchor generation to real data. But they’re not foolproof.
Bottom line:
If Google is a librarian,
LLMs are improv actors who’ve read the entire library.
Sometimes brilliant. Sometimes also wrong.
But when you understand *how* they think — you can use them way more effectively.
Leave your questions or comments in the section below 🥰👇 & share to spread the word!! This concept is simple and yet so important. You guys rock, sending love to you all!
Ben 🇬🇧🇺🇸🇯🇵 retweeted
You should have four emails:
- Work email
- Personal email: family, friends, general stuff.
- Cold email (password manager, exchange, apple ID, recover email, etc)
- Spam email: for e-commerce and random stuff.
You have my axe!
Tonight, Cardiff Castle will light up green to mark Dwarfism Awareness Day. 💚
The illumination celebrates diversity and helps raise awareness and understanding of dwarfism. orlo.uk/S4Qel
ALT Cardiff Castle illuminated at night by bright green floodlights against a dark sky. Caer Castell Caerdydd wedi'i oleuo wrth nos gan fflachlysau gwyrdd disglair yn erbyn awyr dywyll.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
In a somewhat normal world we’d be hauling the CEOs of major TV companies in front of Congress to ask why they’ve built this shit. The answer can easily be Five Eyes told them to, but we can cross that bridge later.
Ok, I just checked this, and its literally running a freaking TensorFlow Lite model on 960×540 images with INT8 quantization every couple of seconds in an attempt to figure out what game you are playing.
It's literally called "alex.tflite" and its literally AlexNet and seems to follow torchvision.models.alexnet. As far as I can tell this does some strange nearest neighbor feature comparisons against a DB and literally doesn't work 99% of the time, you love to see your CPU get wasted every other second by this thing though. It also just seems to dump its results into the void because the consent gate comes later.
Anyways, here's the tf model graph and some dumped captures.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
Sam is so eerily disingenuous here for his gain, with the prime motive being towards regulatory control. Because while what he said is correct in some ways, but it is lies blatantly in others, and in the rest essentially amounts to lying by omission.
I've worked in HW security for more than a decade, leading chip security and AI chips firmware/kernel teams at Qualcomm and Google.
I saw, and worked round the clock in the wake of meltdown, spectre, and many many HW issues.
Some notes:
1. Will "unpatchable bugs" stop without models?
NO. We've always had such bugs being found by security researchers (and black hats) since ages. Models accelerate them. But we've dealt with these things in the past. It is a pure lie to say that "models can find bugs that are outside...what we think a hacker can do"
2. Are HW issues really unpatchable?
Many times, no. You can actually patch a lot of HW bugs too. Through Software workarounds, by disabling hw features that are in the line of fire, by microcode updates, and in many cases even bootroms can be patched through efuses. So, a huge amount of hw bugs actually have a way to be overcome.
3. What about those which are really unpatchable?
You still need them to be known. Because I bet you anything that can be hacked will be found and exploited by the bad actors. But if you know about them:
a. You can remove such hardware from use from critical infrastructure before it gets hacked
b. You can design newer hardware without these bugs to safeguard in the future instead of carrying the same legacy forever and be exploited when you least expect.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
If you've ever wondered why smart TVs are so cheap, this is why.
@log4j rooted his Samsung and found an always-on hot mic, automatic content recognition, geolocation, network mapping, ad targeting and user profiling, shared with Samsung's "400 partners".
A lot of it can be blocked in <15 min, wrote a basic guide below.
What your TV is doing
The main culprit is ACR (automatic content recognition). Your TV screenshots what's on screen, fingerprints it, and sends it home to build your ad profile. Samsung does it every 500ms, LG every 10ms [1].
What is insane: it happens on connected devices too.
Plug in your laptop, your console, your work machine, and your TV can fingerprint that via HDMI [1].
He also found that if your Samsung doesn't have a mic, it'll look for one from a connected soundbar or bluetooth device.
xitter.cf/log4j/status/211376224…
It's on by default, and you likely agreed to it on the setup screen you clicked through in 10 seconds.
Step 1: Turn off ACR
Samsung: Terms & Privacy → Viewing Information Services
LG: Live Plus
Vizio: Viewing Data
Roku: "Use info from TV inputs"
Sony/Google TV: Samba Interactive TV
Menus vary by model, but those are the names to look for. While you're in there, opt out of interest-based ads, reset your advertising ID, decline every optional privacy agreement, turn off voice recognition, and delete apps you never open.
Step 2: Give smart devices their own network
Put the TV, cameras, speakers and vacuum on your router's guest/IoT network. The logic is simple: these devices rarely get patched. If one gets compromised (getting drastically more frequent with AI), it shouldn't be able to see your other devices or home network.
Step 3: Block trackers for the whole house with DNS-level filtering
NextDNS (cloud-based) is easy and has a solid free plan. Pi-hole is a little bit more work if you prefer self hosting. For simplicity we'll focus on the former.
1. Sign up at nextdns.io (free tier is plenty)
2. Privacy tab: add a blocklist (OISD is a good bet) and turn on Native Tracking Protection for Samsung, LG, Roku, Amazon (see attached image)
3. Setup tab: copy your endpoint
4. Paste it into your router's DNS settings as DNS-over-HTTPS/TLS (or use the IPs + "Link IP" if your router only does plain DNS)
5. Bonus: block outbound port 53 except to your router. Some devices hardcode their own DNS to get around you
Then open the NextDNS logs and watch how often your TV phones home. It's eye-opening. If an app or update breaks, find the domain in the logs and allowlist it.
Why they do this
TV prices are down 97% since 2000 [2]. Most of that is better manufacturing and brutal competition. But once margins on the hardware hit zero, the cost moved to you.
In Q3 2024, Vizio lost $6.7M selling TVs and made $115.8M in gross profit from ads and viewing data [3]. They've said on earnings calls that they keep TV prices low to grow the audience they sell to advertisers. Walmart bought them in 2024.
This isn't a conspiracy theory either. Vizio paid $2.2M to the FTC in 2017 for tracking 11 million TVs without consent. Last December, Texas sued Samsung, LG, Sony, Hisense and TCL over ACR. Samsung and LG have since agreed to stop collecting that data without explicit consent [4].
TL;DR
1. ACR off
2. Ads + voice off
3. Smart devices on their own network
4. NextDNS filtering on the router
Sources:
[1] ACR study: arxiv.org/abs/2409.06203
[2] Cost of US consumer goods: aei.org/economics/chart-of-t…
[3] Vizio Q3 2024: sec.gov/Archives/edgar/data/…
[4] Texas v. Samsung: texasattorneygeneral.gov/new…
Ben 🇬🇧🇺🇸🇯🇵 retweeted
My friends were all talking about prepping so I made a survival LLM. A free app that runs an AI mdoel plus 1.5 million offline articles (medical guides, FEMA, survival manuals, wikipedia) entirely on your computer. No internet needed.
brangus.io/survival-llm
Ben 🇬🇧🇺🇸🇯🇵 retweeted
"whatever you now find weird, ugly, uncomfortable and nasty about a new medium will surely become its signature. CD distortion, the jitteriness of digital video, the crap sound of 8-bit - all of these will be cherished and emulated as soon as they can be avoided."
- brian eno
Ben 🇬🇧🇺🇸🇯🇵 retweeted
Claude Code found every photo i "permanently deleted" from my iPhone.
almost 4 years of photos and videos sitting in a hidden cache on my
device. any app with file access can read them.
plugged my iPhone into my MacBook for a backup. had Claude Code running
a security scan from my last post. it flagged something i never asked
it to check. a directory called PhotoData/Thumbnails with over 152,000
files. photos, videos, screenshots. all stuff i deleted.
2022. 2023. 2024. 2025. photos i deleted within a second of taking them.
photos i went into Recently Deleted and cleared manually. photos i
deleted twice because i didn't trust the first time. all still there.
what was sitting in that cache:
a passport photo for a visa application in 2023
bank app screenshots with full account numbers visible
private photos i sent someone and deleted the same night after a breakup
a crypto seed phrase screenshot i took "for a minute" in 2022
my ID and credit card side by side, deleted 10 seconds later
my ex's private instagram stories i saved and "permanently deleted"
in 2024
152,417 files. some at full resolution. all organized by date going
back to 2021.
when you delete a photo on iPhone, iOS removes it from your camera roll
and your Recently Deleted folder. but it keeps a compressed copy in a
Spotlight search index cache. that's how your phone finds photos when
you type a word in search. Apple never clears it. not after 30 days.
not after a year. they told you it was permanently deleted. it wasn't.
checked which apps on my phone had Files and Folders access. 19 apps.
weather apps. QR scanners. PDF readers. a flashlight app from 2021.
any of them could've been reading every photo i ever "deleted" this
whole time.
went from 19 apps to 3 in about a minute.
full step by step is below. takes 2 minutes. bookmark it so you don't
lose it and send it to anyone with an iPhone.
I CHECK EVERY AIRBNB WIFI WITH CLAUDE CODE NOW
takes 2 minutes and it's kind of addictive
check into a place, join the wifi, open claude code and ask "list every device on this network and what each one is"
most of it is boring. the tv, a couple of smart plugs, the router. but you see the whole list, and the one box that doesn't belong stands out fast
last trip one device was from a company that only makes ip cameras. didn't love that
how to do it yourself
1. join the wifi, open claude code, paste the prompt in the first reply
2. it lists every device and flags anything that looks like a camera or a mic
3. if something looks off, lights out and run your phone flashlight over the smoke detectors, clocks and chargers. a lens glints back
you won't remember this at 1am in a strange room. bookmark it now
this only sees your own network, nothing else. just a traveler checking the room they rented
ever found something weird in a rental? what did you use to check
Ben 🇬🇧🇺🇸🇯🇵 retweeted
This is like when the government tells you to eat less meat
Anthropic is now recommending that companies REMOVE unnecessary subagents from their AI systems.
This is a pretty significant shift in agent architecture, with their team finding that a single agent equipped with skills can frequently outperform complex multi-agent systems, and one customer seeing roughly 2x faster execution.
The emerging rules of thumb:
→ Skills: Teach the agent HOW to do something, including procedures, expertise, and instructions.
→ Tools / MCP: Give the agent the ability to DO things through APIs, actions, and live data.
→ Subagents: Use for parallel work, isolated context, or tasks a single agent struggles with.
The interesting part is progressive disclosure. Instead of spawning specialized agents or stuffing everything into a giant prompt, one agent discovers and loads skills and tools as needed.
Their advice is to fold existing subagents into the main loop, turn their instructions into skills, expose their actions as tools, and run evals to see if performance holds up.
As models have gotten smarter, improving agent architecture is becoming less about what you can add and more about what you can delete.
claude.com/resources/article…
All calls to voicemail. Problem solved.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
imagine a fully integrated AI future where being banned means you are now economically useless. everybody around you is a superhuman living in the future but you violated TOS and now are cut off.
your smart glasses that showed you a beautiful utopia? the color has left them. you are forced to live in a bleak gray world. you are forced to look your wife in her actual face and she is not happy with you.
you are digging holes with a spoon while everybody else is building skyscrapers with an army of bots.
this is the real doomer catastrophe
open source is the only way to protect your freedom, your economic viability & your ability to tell these companies to fuck right off.
a few months ago openAI and anthropic were desperately begging the admin to make it legal for them to collaborate. if they got their way, one TOS violation on either platform would send you directly to the sunken place.
Ben 🇬🇧🇺🇸🇯🇵 retweeted
Person who is reverse engineering his tv gets banned from OpenAI
You aren't allowed to stop your tv from spying on your family. You have to ask for permission
Or, maybe, maybe we accelerate
Ben 🇬🇧🇺🇸🇯🇵 retweeted
this account is decompiling a Samsung smart tv and it's actually worse than I was expecting, and I was expecting the worst