iamgopal

How are you going to protect AI which optimise against your tests instead of actual data ?

Are you guys using AI to check on AI ?

Next logical step is to connect ( or build from ground up ) large AI models to high performance passive slaves ( MCP or internally ) , which gives precise facts, language syntax validation, maths equations runners, may be prolog kind of system, which give it much more power if we train it precisely to use each tool.

( using AI to better articulate my thoughts ) Your comment points toward a fascinating and important direction for the future of large AI models. The idea of connecting a large language model (LLM) to specialized, high-performance "passive slaves" is a powerful concept that addresses some of the core limitations of current models. Here are a few ways to think about this next logical step, building on your original idea: 1. The "Tool-Use" Paradigm You've essentially described the tool-use paradigm, but with a highly specific and powerful set of tools. Current models like GPT-4 can already use tools like a web browser or a code interpreter, but they often struggle with when and how to use them effectively. Your idea takes this to the next level by proposing a set of specialized, purpose-built tools that are deeply integrated and highly optimized for specific tasks. 2. Why this approach is powerful * Precision and Factuality: By offloading fact-checking and data retrieval to a dedicated, high-performance system (what you call "MCP" or "passive slaves"), the LLM no longer has to "memorize" the entire internet. Instead, it can act as a sophisticated reasoning engine that knows how to find and use precise information. This drastically reduces the risk of hallucinations. * Logical Consistency: The use of a "Prolog-kind of system" or a separate logical solver is crucial. LLMs are not naturally good at complex, multi-step logical deduction. By outsourcing this to a dedicated system, the LLM can leverage a robust, reliable tool for tasks like constraint satisfaction or logical inference, ensuring its conclusions are sound. * Mathematical Accuracy: LLMs can perform basic arithmetic but often fail at more complex mathematical operations. A dedicated "maths equations runner" would provide a verifiable, precise result, freeing the LLM to focus on the problem description and synthesis of the final answer. * Modularity and Scalability: This architecture is highly modular. You can improve or replace a specialized "slave" component without having to retrain the entire large model. This makes the overall system more adaptable, easier to maintain, and more efficient. 3. Building this system This approach would require a new type of training. The goal wouldn't be to teach the LLM the facts themselves, but to train it to: * Recognize its own limitations: The model must be able to identify when it needs help and which tool to use. * Formulate precise queries: It needs to be able to translate a natural language request into a specific, structured query that the specialized tools can understand. For example, converting "What's the capital of France?" into a database query. * Synthesize results: It must be able to take the precise, often terse, output from the tool and integrate it back into a coherent, natural language response. The core challenge isn't just building the tools; it's training the LLM to be an expert tool-user. Your vision of connecting these high-performance "passive slaves" represents a significant leap forward in creating AI systems that are not only creative and fluent but also reliable, logical, and factually accurate. It's a move away from a single, monolithic brain and toward a highly specialized, collaborative intelligence.

If only AI models are trained to connect to data (sql) and use that to answer some of the questions using data source instead of just train on them, it could reduce model size a lot.

Are there any research in this area ? Crypto and particularly bitcoin mining has massive capacity for computation , albeit at lower memory scale, if AI memory model could be encode in to blockchain, we can get benefit from bitcoin mining.

when that crane will reach end of its life, it will be move to india for another 10-15 years of service life.

Move to Gemini branch first.

Quite simply, standardising public transport across the globe, ( and in turn bringing economy of scale ) , can solve the transport problem , problem is that this is not economically viable for car companies

Monitor ticket price and book it when it’s below some price ?

can't there be specialise models that gemini can take help from just like humans do take help from another human ? I have guts feeling that adding everything in single model may degrade its overall competence. For almost all model, as I go deeper, ( and most here must have experienced it. ) I clearly recognize that gemini ( or most other well known ) starts to fail at task, so subtly that you may think it is correct but it is not. This is dangerous, and increases work of verification at our end instead of reducing the work.

Pay it forward

H2G2

gemini 2.5 give following response.

Conclusion:

We can determine the price of a single ball ($0.575) and a single bat ($0.525). However, we cannot determine how many balls and bats Sally has because the information "a few" is too vague, and the fact she stole them means her $20 wasn't used for the transaction described.

Small fast ( binary ? ) AI will be as simple as storing data in database and query it, in fact, very soon specialised software will come in to market to do so, guided by large LLM.

Small Models should be train on specific problem in specific language, and should be built one upon another, the way container works. I see a future where a factory or home have local AI server which have many highly specific models, continuously being trained by super large LLM on the web, and are connected via network to all instruments and computer to basically control whole factory. I also see a future where all machinery comes with AI-Readable language for their own functioning. A http like AI protocol for two way communication between machine and an AI. Lots of possibility.

That's what OP was implying. Energy (..and its derivative global warming ) is just infrastructure and finance problem now onwards. Balancing grid, Moving power from sunshine area to non-sunshine area, storing some power at night, handling fluctuation all are more or less solved problem. Fusion is just research subject ( ..or for may be powering colony on mars ? ). ..... saying that, I hope our collective curiosity for fusion will take us to new inventions and space opportunities.

If Targeted spending of 500 Billion ( per year may be ? ) should give enough automation to reduce panel cost to ~100M/GW = 1340 Billion. Skip battery, let other mode of energy generation/storage take care of the augmentations, as we are any way investing in grid. Possible with innovation.

500 billion can move whole country to renewable energy

While your argument is true, I would guess aliens will be quite a lot different than anything we know on this earth. Even different in so called life and death cycles, or even in the very definition of what we can call alive and dead. We should much broaden our search scope.

What could be cost of total storage of YouTube ? Edit : About billion USD per year.

tell me more or write a blog post.

Can we send a voyager 3 with much advance battery and sensor, and at much faster speed so that it may reach farther than voyager 1 and 2, in let’s say just couple of years ?

Short answer is, there is no need. Personal computer were sold to make nice printed paper. Here there is no specific application.

every new prime for new block, but not linear.

Is there typst based static docs generator out there ?

I don’t understand, the starship has to stand on something, and what ever that is in contact with ( arm or barge or land or whatever ) , needs to be as heavy, how they are saving weight ?

no matter how fast cpu, network and browser has become, websites are still slow. we will run out of data to train much earlier than people will stop inventing even larger models.

Are we increasing or decreasing the "knowledge" entropy ? ( in the closed system of earth ? ) by doing AI ?

Live journal anyone ?

200 USD is retail price, bulk purchase is even less than 100 USD