BASELINE retweeted
Tacit know-how is the most important part of human knowledge
And it's the part AIs don't have
Big tech is preparing to capture it on an industrial scale
If we don't act to protect it, the consequences will be enormous (see clip below)
There is one way to fight back: Prometheus
@Dr_JohnFletcher described Prometheus on 10 February in this interview: youtu.be/3q1RhqoV3mw?si=-tC1β¦
See here for the full Prometheus vision: xitter.cf/Dr_JohnFletcher/statusβ¦
Yesterday, Prometheus Swarm, the first step towards realisation of this vision, was Open Sourced: xitter.cf/tigfoundation/status/2β¦
Find out more at tig.foundation
This is something that @Dr_JohnFletcher has been warning about for a while now..
Tacit Knowledge
I'll admit, John opened my eyes to this as I hadn't previously given it too much thought..
Most people view their relationship with OpenAI and Anthropic as a one way thing..
We prompt the model with a problem and it gives us back an answer.. pretty simple
But every time we interact with these models, we also reveal something about how we think
What to try.. what to avoid.. why certain approaches fail.. the way we ask questions.. all that intuition that we've built through years of experience
That is Tacit Knowledge..
Its the valuable, unwritten expertise that can't be found in papers or textbooks.. but its an extremely valuable ingredient when it comes to innovation
Not every prompt instantly trains the model.. the deeper issue is that these massive AI companies are becoming embedded within millions of workflows
And over time.. this gives them extraordinary visibility into where these valuable problems exist and how experts solve them
It also gives them an insight into which industries are ready to be disrupted next
Which means.. the very company supplying the intelligence could absorb enough knowledge and market insight to compete with the businesses, or even partners using it
It then becomes a really powerful flywheel..
An expert uses a model
>
The model learns from the way they solved the problem
>
The company supplying the intelligence grows stronger capabilities
>
Those capabilities then become competing products against the expert or business using it
Its a real issue that inevitably leads to all power in the hands of a few morally questionable centralised mega companies
This is one of the core problems $TIG is trying to address..
#Prometheus is an open algorithm discovery system where swarms of AI agents explore, code and test thousands of ideas in parallel
Experts are able to guide those agents with their own tacit knowledge..
But, the key part is..
Without having to publish or surrender the underlying expertise to the wider swarm or @tigfoundation.. which means the tacit knowledge itself doesn't need to be shared
So the knowledge can still influence the algorithm produced.. but the expertise stays locally with the contributor
Instead of that tacit knowledge being absorbed into a closed corporate flywheel.. $TIG's building an open one
Private expertise from the human
>
AI agent discovery through #Prometheus
>
Which leads to better algorithms
>
They're independently benchmarked and validated
>
Rewards are then routed back to the contributors
What gets shared is the breakthrough.. not the tacit knowledge that helped create it
This results in the value flowing to the researchers and experts who helped create it.. rather than exclusively to these AI companies
With the added bonus of their private tacit knowledge remaining with the contributor rather than becoming public property.. or being handed over to OpenAI or Anthropic
The goal being rewarding those who are truly changing society for the better..
While preventing humanity's accumulated knowledge from being willingly handed over to these centralised companies who have the potential to abuse it for their own gain
$TIG
BASELINE retweeted
Prometheus opens algorithm mining up.
Anyone can run it and compete for the rewards.
BASELINE retweeted
sounds important $TIG
Most people think you can't capture value from Open Source because open means people will always take it for free
But as Phil explains below, this isn't true. It's never been true, at least for larger companies, who are the vast majority of the market
So what's the real issue?
The way to capture value, and use that value to fund further open development, was identified 25 years ago
In "The Magic Cauldron", Eric Raymond explains whats required: a market to price code econ.ucsb.edu/~tedb/Courses/β¦
But no one ever figured out how to create such a market
In 2016, I had the idea that proof of work could create a market for a very particular type of open code..
Algorithms for "hard to solve but easy to verify" problems
But how useful is this in the real world?
It turns out, it's everything we need
BASELINE retweeted
Most people think you can't capture value from Open Source because open means people will always take it for free
But as Phil explains below, this isn't true. It's never been true, at least for larger companies, who are the vast majority of the market
So what's the real issue?
The way to capture value, and use that value to fund further open development, was identified 25 years ago
In "The Magic Cauldron", Eric Raymond explains whats required: a market to price code econ.ucsb.edu/~tedb/Courses/β¦
But no one ever figured out how to create such a market
In 2016, I had the idea that proof of work could create a market for a very particular type of open code..
Algorithms for "hard to solve but easy to verify" problems
But how useful is this in the real world?
It turns out, it's everything we need
BASELINE retweeted
This was a fantastic chat with @BaselineAI from 3 months ago.
If you haven't watched it, now it a good time as we discuss things that are only coming to pass now.
The clear path we're on, given current incentives, is:
1. Use AI tools like Claude Science to capture know-how/tacit knowledge (the knowledge that AI does not already have, because it was never written down)
2. The tool improves due to having this knowledge. Quickly becomes so good it is indispensable, meaning even scientists that object to the capture (because they know where it leads) cannot realistically opt out.
3. Once enough know-how is captured so tool no longer needs the mass of human researchers, it is immediately declared "too powerful" and a "national security risk" and public access is withdrawn.
4. It is then used to control the world, a major component of which is stopping any research that could lead to AGI.
Is this what we want? Has anyone heard the above scenario proposed/discussed before?
If not, why not? @beffjezos @elonmusk
This is a great discussion with @Dr_JohnFletcher from $TIG
A lot of important, juicy topics they dig into but one thing that stuck out to me..
Everyone is individually incentivised to use AI because its faster and makes them more productive..
But all they're doing is feeding that tactic knowledge back into centralised systems
Which means..
1. You opt out.. but you fall behind
2. Opt in.. but you help build the thing that will likely replace you later
This is why.. there needs to be systems where incentives are redesigned at a fundamental level..
So that value flows back to those who contribute, instead of leaking away to one company
This is why we $TIG..
youtu.be/3q1RhqoV3mw?si=6yvxβ¦
Highly recommend giving this one a listen π
$TIG
BASELINE retweeted
calling all cypherpunks..
for one more mission.. $TIG
Replying to @MachSpeedMkts
We may be closer to agreement than it appears. To be clear: I am not claiming my argument is established beyond reasonable doubt. The evidence I have presented is not sufficient for that.
But that is not the right standard to apply here. The question is not "has this been proved?" but "is the mechanism plausible enough, and the consequences severe enough, that we should act?"
Given what is at stake (a possible monopoly over the means of mathematical discovery) I think the burden of proof runs the other way.
Those who are capturing this data should be asked to demonstrate that the mechanism described will not, in fact, produce the outcome described.
On the question of what to do: I sketched out a proposal in the second half of this interview. The relevant part starts at around 23 minutes youtu.be/3q1RhqoV3mw?si=iWNoβ¦
BASELINE retweeted
if this doesn't go viral
dead internet theory is proven
biggest threat humanity's ever faced
no one even knows it's happening
$TIG @elonmusk @DreadBong0 @satyanadella @tigfoundation @0x_Asuka
BASELINE retweeted
2003 might be the worst year to be born
2008 - parents lose all their saving
2011 - too young for bitcoin
2020 - senior year in zoom
2021 - college in lockdown
2026 - get replace by AI
2038 - might die in the space war
BASELINE retweeted
Replying to @BaselineAI
I agree assistants are getting more capable. The next step is measurable reliability, things like task completion rate and correction loops matter more than wow demos.
BASELINE retweeted
Great name π
Trung Phan@TrungTPhanFeb 15π¨π¦
CanadaConnected via United States App StoreAccount-level information, not a live location or per-post device.
SpaceX has a custom version of Grokβ¦and itβs called Spok. Glorious.
BASELINE retweeted
The most beautiful 29 seconds in modern engineering.
Rockets donβt just launch anymore.
BASELINE retweeted
Can #AI End Biases In Mental Health Therapy?
by Eugene Klishevich @Forbes
Learn more: buff.ly/3zQWjaS
#ArtificialIntelligence #MI #MachineLearning #HealthTech #TechForGood #Tech
@paula_piccard @sallyeaves @yuhelenyu
BASELINE retweeted
Difference Between #ChatGPT and Gemini
by James Howell @101Blockchains
Learn more: buff.ly/3NgiTga
#BigData #AI #ArtificialIntelligence #DataScience #Tech
cc: @space_mog @iainljbrown @yuhelenyu
BASELINE retweeted
The Future of Security with #Drones
via @FrRonconi
#Robotics #AI #MachineLearning #Tech #Technology #Automation #FutureOfWork
cc: @pbalakrishnarao @karpathy @chr1sa




















