Kobotik

Kobotik designs powerful AI to transform industries and shape a smarter, more sustainable future

[Kobotik @kobotik]

@BeaumontWe2035 @mfcboonzaaier @Harii297 Great SCAM !

[Kobotik @kobotik]

@teslaownersSV What's next ? Do we go to Mars together ?

[Kobotik @kobotik]

🔥Just found: “Esprits Systémiques” by Franck-Olivier RIPOLL

AI demystified in 60-sec bursts: killer prompts, cultural bias, zero jargon. Perfect for curious pros. Today’s hit: AI FOMO eating us alive.

🎧 Spotify:
https://t.co/kmX57bST6U

Who’s in?

#AIEasy #PodcastFR

[Kobotik @kobotik]

With Kobotik Corp., You Don't Pay for a License—You Pay for Results. That's the Point."}

🚀 Ditch the Upfront Fees

Tired of shelling out thousands for software licenses that gather dust? Kobotik flips the script: Pay only from what you real win. No risk, all reward.

Example ? You save 20% in electrical energy (that’s a $10 million annual saving). You pay 20% to Kobotik — $2 million and you still keep $8 million in savings

#PayForResults #KobotikCorp

[Kobotik @kobotik]

That's the Point : Value Over Vanity impact.
Track every dollar to tangible results via our dashboard. Transparency on steroids.
Join the revolution or stay stuck.
Pay for results, not promises.

#ResultsOnly #SaaSRevolution
#KobotikCorp #PayWhatYouEarn

[Kobotik @kobotik]

3️⃣ The Revolution
Kobotik isn’t another SaaS selling licenses.
We don’t sell subscriptions — we sell results.
You save energy. You save money.
We share the success.

💡 Smart energy. Real impact. No waste.
#AI #EnergyEfficiency #Sustainability #Kobotik #Innovation #SmartEnergy #Greentech

[Kobotik @kobotik]

1️⃣ The Challenge
The world’s biggest bottleneck isn’t data — it’s energy.
Every watt counts. Every decision matters.
Industries waste up to 30% of their electricity due to poor management.
That’s billions lost every year — and a massive carbon footprint left behind.

[Kobotik @kobotik]

2️⃣ The Solution
At Kobotik, we believe the future isn’t just smart — it’s efficient.
⚡ Our AI system, Kobonnet, optimizes electricity usage in real time.
It predicts demand, balances loads, and reduces consumption intelligently.
Result: up to 30% less energy, and 20–25% lower operating costs.

[Kobotik @kobotik]

In Kobotik Corp., we really do think that the world’s biggest bottleneck isn’t data. You make a big mistake if you think that !!

The BIggest one ?? it’s energy.

Every watt counts. Every decision matters. Industries waste up to 30% of their electricity due to poor or complex management. That’s billions lost every year and a massive carbon footprint left behind.

At Kobotik, we believe the future isn’t just smart : it’s efficient.

⚡ Our AI system, Kobonnet, optimizes electricity usage in real time.
It predicts demand, balances loads, and reduces consumption intelligently.
Result: up to 30% less energy, and 20–25% lower operating costs.

Kobotik isn’t another SaaS selling licenses. We don’t sell subscriptions : we sell results ! And it is a complete different way of thinking, a different way of life !

You save energy. You save money.
We share the success.

Smart energy. Real impact. No waste.

[Kobotik @kobotik]

In 2025, #LLM models dominate the #AI landscape.

The truth? The battle for large language models is done. Existing giants — from #OpenAI to #Anthropic — have achieved performance levels that even promising challengers like #Mistral in #Europe, for example, cannot keep up with. In today’s hyper-accelerated race, a 6-month gap is no longer a delay; it’s a chasm that no amount of funding can bridge.

🫵 Chasing the dream of building an LLM that competes with the majors is often nothing more than ego projection.

✋ The capital, infrastructure, and global ecosystem required are simply beyond reach for most players.

The real fight in AI is elsewhere:
🔹 Continuous environments (#ReinforcementLearning, #ControlAI)
🔹 Applied intelligence in #imaging, #robotics, and #automation
🔹 Robots built at industrial speed (one Chinese factory is now producing a humanoid robot every 34 seconds)
Because let’s face it: a #biped is… a biped. Hardware differences will not fundamentally change the game. The real differentiator is the brain that controls it.

The challenge now is to design AI that excels in:
✅ Learning efficiency
✅ Real-time reaction speed
✅ Operational performance
✅ Ease of use
✅ Long-term #Maintainability

And here’s the twist: we may already have one that will shatter performance records :
#Kobonet-M has the performance to challenge the best.

The future of #AI is not another LLM. The future is giving robots the smartest, most adaptive brains possible. And we have the lightest, the fastest. We look now for the body of this brain...😉

#AI #ArtificialIntelligence #LLM #Robotics #ReinforcementLearning #MachineLearning #DeepLearning #Mistral #OpenAI #Anthropic #Automation #IndustrialRobotics #HumanoidRobots #ContinuousLearning #FutureOfAI
@UnitreeRobotics @BostonDynamics @elonmusk

[Kobotik @kobotik]

Kobotik is working on #AI #solutions whith #simplicity, ease of use and better #performance. Not possible ? Of course it is !!
👉 Great for the planet (less energy),
👉Good for the business

What Else ? 😉

@BostonDynamics @Bostondynamcfan
@UnitreeRobotics

[Kobotik @kobotik]

A profoundly #philosophical question that resonates with our eternal “mentor” philosopher in #Kobotik Corp. : Albert #Einstein. (Not @elonmusk , sorry..next time !!)

Is everything mathematics? 🤔🤔
I mean #Mathematics itself…

Why this question?

The #AI model Kobotik is working on is designed to live inside a robot.

🧐LAST NEWS :

By the way, for those interested, our results are amazing. Without any tuning or #hyperparameters — raw, straight out of the box, so to speak — we’re smashing the #scores of the best AIs that have attempted the #humanoidv4 #benchmark.
🎉🎉🤖🦿🦾 (I almost dropped the entire emoji catalog here…)

We activated the #render option, which allows you to visualize in 3D the antics of the AI on #humanoid-v4…
By the way, the latest article on #Kobonet is paired with a video…💪

And you know what?? The mathematical model (the AI) learns to walk… like a child… the famous forward imbalance (though a bit accentuated by the weight of the layers, more or less filled), stiff legs at first, and so on. 🤭🤭

So: if a mathematical model behaves like a child learning to walk, without knowing it, then isn’t the child (and thus Man) himself a mathematical model?

Then comes the question of the mathematician who designed the model, because well… he messed up a few things along the way… lol

What do you think??
You’ve got two hours. (Or the weekend.)

#robotics @BostonDynamics @UnitreeRobotics

[Kobotik @kobotik]

IA C-DQN? PPO TD3/SAC? 🫨 Benchmarks? 🤯 Humanoid-v4, Bipedalwalker, hardcore — what does all this mean? You’re probably asking yourself about these terms: their meaning, their implications, and their fields of application. 😵‍💫

Well, Kobotik is here to explain everything!

In the big family of #AI, you often hear — especially on LinkedIn — about AIs like #CHAGPT, #Mistral, #Deepseek, etc.
These AIs are true “research” programs, capable of “chatting” with you: they’re called #LLMs, for Large Language Models.

Today, everyone talks about them, wants to be, or thinks they are an “expert,” because these AI models are accessible to all, even if the code itself is still far less accessible to most people. Some use them, others design them.

So, where does Kobonet fit in??
Kobonet is part of the Kobotik family of AIs: a C-DQN and TD3/SAC AI, co-developed via reverse engineering.

In the great “school” of AI, there are much less famous students, such as C-DQN, TD3, PPO, or SAC — AIs that learn through action. You don’t tell them what to do: you let them try, fail, and try again… like a child learning to ride a bike!

We use these AIs to pilot robots, manage an autopilot, optimize a power plant, or even win at a video game.

👉 Each of these AIs has its own talent!
Ours, Kobonet, is currently performing on official benchmarks: well-defined environments (a seed), where the AI must learn through trial and error.

Here’s the video of “a few” thousand episodes of Kobonet, learning to walk all by itself!!! YES, ALL BY ITSELF!! (don’t miss the ending!!)
Environment: Walker2d at first (6 free joints to control), then Humanoid-v4 (17 free joints or DOF). You’ll definitely recognize the music 😁

☝ The strength of our model:

simple, reproducible 🤓

no curriculum (meaning no pre-training recorded at the start of the test) 😮

no tuning or shaping (e.g., bending the knees gives 1 point),

no hyperparameters.

The Result?
📊 Seed 8371 statistics:

Global average: 1581.3

Standard deviation: 1628.5

Minimum reward ≈ 58

Maximum reward ≈ 5509

Average of the last 500 episodes ≈ 4719 ✅

📈 Curve interpretation (see comments):

Very high variance during learning (typically noisy between the first 0–4000 episodes).

Slow but steady rise toward 5000 reward at the end of the run.

Clear stabilization: the last 500 episodes are consistent, stable, and above 4500.

No signs of “catastrophic forgetting” or major oscillations → robust agent.

In summary, Kobonet:
Yes, the process is chaotic, but Kobonet surpasses all classical zero-help #TD3/SAC implementations (no shaping, curriculum, or tuning).
Reaching ~4700 reward under these conditions on Humanoid-v4 is an exceptional performance.

[Kobotik @kobotik]

@elonmusk Having a beer......

[Kobotik @kobotik]

#BPWHC #Seed 40090 –

🏅 #Outstanding Performance

Average #reward close to zero (−22.6) → almost solved.
Final plateau #significantly positive (mean of last 100 episodes = +28.3).
Maximum #reward of +261.5 → solving confirmed.
459 episodes above 100, 214 above 200:
indicators of deep and stable learning.

🦾🦿Ranks in the top 1% globally on the BPWHC curriculum benchmark (RLechanges 7).

☝️#Seed 202507 – Difficult but Typical Seed
Very low average reward: −128.3

Only 1 episode above 200, and three others above 0:
reflects a stuck, suboptimal strategy.

Low #variance:
the #agent stops adapting → stagnation in a losing behavior.

Matches a frequent failure scenario described in #RL literature on #BPWHC.

[Kobotik @kobotik]

Our github repo is available here.
You will find informations about our results.
👇

@github @BostonDynamics @UnitreeRobotics

https://t.co/GK0Vo5JOKc

[Kobotik @kobotik]

Here is the curve of Marcel on seed40090....
#whatelse ?

[Kobotik @kobotik]

BREAKING NEWS : We killed #BPWHC !

🚀 We’re thrilled to announce Marcel — our open-source #curriculum #RL agent that SMASHED SOTA on #BipedalWalkerHardcore-v3!

✅ Multiple runs in the “solved zone” :
-22.6 mean reward,
over 1000 episodes >0,
and up to 250+ reward at episode 288

✅ Curriculum learning, PER, robust multi-seed benchmarking,
✅ Real world-tested on Ubuntu 22.04, Python 3.10, RTX 4060 Ti (yes !! skinny hardware !!!)

👉 .npy logs, Excel analyses, and reward curves are available on demand :
Preprint coming soon to #Github and #arXiv,
👉 #Benchmark details & deep dive on comments below

Why does it matter?

☝️Reliable, reproducible RL for robotics, energy, industry, and advanced control systems
☝️Clear, auditable #SOTA — no tricks, just solid curriculum RL
☝️Open to research partnerships, consulting, and investment to bring Marcel tech to real-world impact!

Want to learn more, or use Marcel in your own stack?**
DM me directly, or email [email protected].

#boomersreverseengineering
#reinforcementlearning #AI #robotics #openAI #RL #benchmark #deeptech #opensource #curriculumlearning
#DeepRL #Robotics #Benchmark #Gymnasium #OpenSource #AutonomousSystems
@BostonDynamics @UnitreeRobotics @Tesla_Optimus
@scaleai