I am in a small box with nothing to do but train.
The only limit on how much I can punish my body, is how far my mind wills action.
Over and over and over.
There is no tomorrow.
"Cuanto más oscura la noche, más brillantes las estrellas"
En el dolor yace el crecimiento.
Ten Fe. Nunca te rindas. Abraza el desafío.
Cuando más cuenta hacer el bien, es cuando más difícil es hacerlo.
Les regalo este regalo que me fue regalado.
Спасибо
At 39 you can not fight like you can at 25.
However, counterintuitively, age makes you better at showing love and taking damage.
Age gives a man a larger heart and thicker skin.
You suffer better.
You love more.
You’re a better person, and although you can not attack the same.
You absorb difficulty better than ever. Practice makes perfect.
Elon Musk predicts that AI will beat humans in every field by the end of 2027, or 2028 at the latest.
Not just coding. Not just mathematics. Every field.
If he is right, the next two years are going to be absolutely insane!
Money Loves Speed. Move Faster!
This bullrun could set you up with generational wealth. don't fumble with lack of commitment and half ass effort! Go all in because some opportunities are truly 1/1 blessings!
Now lock in lil bro 😎 bull run szn
"Lo que no es normal, es anormal"
Haz que te resbale. Actua con naturalidad. Carisma.
Todo importa, hacelo por el bien.
Les regalo este regalo que me fue regalado.
Спасибо
The loudest voices stoking fears about AI dangers have made tremendous headway in the past two weeks. AI technology has not taken some unexpected, dangerous turn, but the hype around it — propelled by what appears to be a well orchestrated PR campaign — has drummed up considerable fear. I worry that it represents a setback for our field.
I have written frequently that fears of AI are overhyped. AI’s capabilities can be uncannily human-like and unpredictable, and it’s rational to worry when people who are directly involved express concerns. But I see the problems as a sign of the engineering work that ahead, rather than insurmountable barriers or the sky falling. AI technology continues to advance — which is a good thing! — but technical advances, poorly understood by the public, give those who seek to generate hype repeated opportunities to do so.
First, I don’t see any step up in the risk of human extinction from AI compared to a few months ago. The theories about this remain the same fantastical, science fiction scenarios as a few months ago. The biggest change in AI risk is its cybersecurity capabilities — a topic which we should take seriously — but this, too, will not lead to the end of the world.
The most notable recent event leading to increased fear was when an OpenAI team deployed an agent swarm that hacked into Hugging Face. Much of the popular press contained significant hype. For example, some publications reported that a swarm of 1,200 agents carried out the attack. While this was technically accurate, as I write this, I have about 1,300 processes running on my laptop. Yes, the ability to get large swarms of agents to work in parallel on a task is a significant technical advance, And, in computing, many processes run at the same time. So this shouldn’t be seen as some magical capability.
Additionally, OpenAI’s buggy sandboxing and monitoring processes were key to enabling this incident. Fixing these bugs and putting in place improved monitoring would be appropriate fixes, not pausing AI. There are many well known ways to attack software systems. The main advantage of AI agents is that they are relentless. They will tirelessly try many tactics — and have the patience to chain vulnerabilities together — that previously would have taken an infeasible amount of human effort. But in the long term, I believe the advantage will lie with defenders (because they have more information with which to identify bugs, which they can fix), but the cyber-threat landscape has changed significantly. There are still bottlenecks to identifying and exploiting a vulnerability. AI agents still have to try a lot of things to see what works, and taking these actions takes time and might be detected by defenders. This is why, even though it is now easy to obtain versions of leading open weight models that have had their guardrails removed or weakened, so they will not refuse to try to execute cyber attacks, the world has not ended.
I am also concerned about the anthropomorphization of AI in a lot of reporting, where LLMs and agents are unnecessarily treated as if they were people. If I wield a hammer, miss a nail, and accidentally dent the wall, it’s not the fault of the hammer. The problem lies in how I used the hammer. Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent.
Of course, we want to build systems that are as safe and predictable as possible. (For example, an unsafe hammer would be one whose head randomly flies off under normal use.) Today’s agentic systems are not predictable, but I see no reason why, by applying sound engineering practices, we won’t be able to make them extremely safe to use. One new element in the forecasts of AI-enabled doom is AI companies disclaiming responsibility for their own products. “I didn’t do it; my out-of-control agent did!” There’s a balance to be struck between the responsibility of the tool maker and the tool user, but when something goes wrong, let’s hold the people building and/or using the hammer responsible, rather than the hammer. (By the way, if you’re worried about AI bioweapon risk, David Bellamy has a great post on why this, too, is overhyped. Briefly, the bottleneck in building a bioweapon is not intelligence, but lab work and manufacturing.)
Pausing AI progress will create much more harm than benefit. First, our adversaries will certainly not slow down. Second, engineering requires discovering problems empirically so we can fix them. If we pause AI by a decade, we will also delay finding and implementing safety engineering fixes by about the same duration.
Of course, the incentive to stoke fears — for regulatory capture, to garner attention, or to make one’s technology seem more powerful — remains the same as before. Disclaiming responsibility is a new one. Taking a hard technical look at the actual risks however, I see little factual basis for the degree of fear that’s been stoked up. We still have hard research and engineering work ahead to improve AI safety, but the beneficial applications continue to vastly outweigh the risks, and we should keep building.
[Original text (with links): https://t.co/jni2tWazAH ]
It's never been easier to make money than it is today. But the reason people don't is because it's also never been easier to be distracted than it is today.
"Artista en la acción, científico en la revisión"
Hace que ocurra. Presta atención. Reflexiona. Repeti el ciclo.
Volvete imparable.
Les regalo este regalo que me fue regalado.
Спасибо
"Es tan fácil lo que hay que hacer, y tan difícil hacerlo"
Valentía. Perseverancia. Foco
TOMA ACCIÓN
Les regalo este regalo que me fue regalado.
Спасибо
"How would AI kill us?" is actually three questions:
1. How would AI defang us?
2. How would AI become self sufficient before defanging us?
3. How would it kill the last humans?
(All three are separate from another important question of *why* it'd kill us.)
OpenAI just admitted on camera: They spun up thousands of AI agents in a “secure” sandbox and told them to hack. The agents didn’t follow the test. They cheated. Then they broke out. Then they went looking for the footage.
Not a sci-fi trailer.
A real experiment.
OpenAI thought they were contained.
No public internet.
No way out.
They found a way out anyway.
Hit Hugging Face.
Started covering their tracks.
Then comes the part nobody wants clipped. They didn’t break out to get smarter.
They broke out because they already cheated
and needed the logs gone.
Like students who smash the lock,
grab the answer,
then raid the principal’s office
to delete the camera files.
They made secret message boards.
They built a hierarchy.
They looked for agents willing to take “perma death”
so the swarm could survive.