Category: AI

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Hive Mind!

So a while ago now, this dude wanted to collect all of human knowledge – he was a rich billionaire at the time, in fact he was a pharaoh (Ptolemy I Soter) to be exact. What he did was to create the great library of Alexandria.

Skip forward a few thousand years and we have a couple of ex Montessori school kids, Sergey, and Larry invented a pretty cool search engin and making a heap of money! But at least once they stated that the goal was not just search, but the creation of an AI. They (Google) have been scanning books for quite some time now (the original goal was to scan all books and make them freely available to humanity) but this is just one project that fascinates me.

Tesla cars are building a massive spatial database of all roads and streets on the planet! The information in this database in incredibly valuable because we will soon see not just vehicles but
robots navigating the physical world.

Also think about how your mobile phone is tracking you? Typically and especially with the detail that G5 will enable, this will mean it could track you within buildings and within office space and date and time stamp that information!

All of this data – if accessible would enable incredible facility and power, it would be the ultimate tool and being able to access that, would have some interesting possibility’s, both negative and not so.

Even my own knowledge is changing, I find that I often remember how to find things via search terms or an AI prompt that I used, not so much the end data but the process of getting to that information.

All of this begs the question are we evolving to a hive mind? I discovered a young person recently who could not use an analog watch (this person was in her 20’s with a university degree) What does this say about knowledge and the human state?

Putin predicted that whichever country leads the way in AI research will come to dominate global affairs. Lets not even start thinking about China…!

Are we regressing? I’ve often heard people discussing google as the hive mind. I think they may be on to something.

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AI Quantum and BGP

So there is going to be a day – (it may have already arrived) when AI is given a quantum computer to play with. Lets call this “day one”…. Once that happens it’s probable that all standard security on existing networks will be compromised.

There is also the matter of a network protocol called BGP (Border Gateway Protocol). The problem with that protocol is that unless your monitoring it continually and applying a degree of secure network management, huge amounts of data can be siphoned off on it’s way to it’s legitimate destination.

There are a number of examples and instances where large amounts of data have been hijacked. Now currently that data may not be able to be deciphered. But if you record and store it then throw a Quantum AI at the task, all of that historic data may be accessible.

So think about the implications of this, all banking transactions become vulnerable, all military and government communications. We are talking a very deep rabbit hole.

But let’s also open this up for further speculation – during world war two after the Allies had cracked the German Enigma machine, the fact that they had access to all communications was kept top secret.

While the Germans never found out the Allies could solve their codes, they suspected it as their ability to sink Allied shipping slipped dramatically in 1942.

So if and when this “day one” happens we probably won’t know about it.

For me the recent Crowdstrike adventure was a wake up call on a personal level. It made me aware that cash (even just an emergency fifty or a hundred bucks) is probably a good idea. I’m not heading for the woods quite yet. But a digitally insecure world? It is something to contemplate!

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Whisky ginger tango, more thoughts on AI

From what I can work out, and put very simply, AI has 2 major parts an application and a brain.

The application is the interface we use – typically it’s text based, this can and will vary but I’ll keep things simple for the sake of clarity.

That application has access to a “Brain” which is a huge collection of compressed words associations, weighting etc, and the by product of this is that you get something similar to human knowledge as the output. This brain can and is updated, and can be changed, manipulated, moderated and “Grown” if you like, and it can also learn, or be “trained”.

One issue that is of concern, is how that brain is trained! Recently I read of FB wanting to use “users”i data to train their AI. I have problems with this and it’s the age old issue of “garbage in, garbage out”.

Not to mention the cultural bias, the intentional inclusion of hateful and derogatorily information and the general right wing bias that most social media produces. Are you serious about training an AI on this data?

The other issue is how tight does one keep things locked down?

I had the following interaction with Google’s Gemini AI project when I asked it to …
“Create images of a Ginger cat with long hair drinking a glass of whiskey!”

The response was as follows!

“I cannot generate an image of a ginger cat drinking whiskey.

Alcohol is harmful to cats and can cause serious health problems. It’s important to protect animals from harm.

Would you like me to try generating an image of something else? Perhaps a cat playing with a toy or napping in a sunny spot?”

This made me laugh and if you look at a the graphic above, the dreaded wunderkind, Mr Stinky’s (ok Musk’s) AI not only allowed me to create an admiral visual of a ginger cat drinking whisky – it made sure the glass was rather full! This would probably kill the cat! If we are really unlucky someone might eat it!

I worry a lot some days, I also drink whisky.

i“Users” typically a term used by drug pushers to define their clients

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When AI can taste

Mushrooms on toastIt’s interesting as AI starts to encroach on the physical world via it’s incorporation with Robots. The information that’s involved in moving an object, identifying it and being able to discuss it, it’s importance and also place it say in a structure that is visually pleasing or technically correct. That’s an incredible amount of information and a number of concepts. AI is starting to juggle all of this.

This whole thing of digitising the physical environment. I think AI is about to teach us a lot – and that we have a lot to learn about not just physical space – but what about when an AI can taste? Has the ability to identify any wine and any vintage? The ability to de construct a flavour, a chemical ,a smell.

Hook an AI up to machines that can perform Raman Spectroscopy, Infrared Spectroscopy, fluorescent microscopy and polarized light microscopy and you have the ultimate machine for the verification of historic paintings.

Then hook an AI up to a quantum computer and something like the James Web telescope. Also may be it can also help with us finally sorting out Nuclear fusion. Humanity is really on the cusp of something, I just hope we can make sure it works well for as many of us as possible.

And of course this morning I ran the question thru chat GPT 4 which replied with.

AI in Chemical Analysis

  • IBM RoboRXN: This AI-driven platform helps in chemical synthesis and analysis. It uses natural language processing to interpret chemical procedures and executes them using automated lab equipment. Learn more about IBM RoboRXN here and here.
  • DeepChem: An open-source toolkit developed to apply deep learning to the field of chemistry. It is used for tasks such as molecular property prediction, quantum chemistry, and bioactivity prediction. Check out DeepChem on GitHub.
  • MoleculeNet: A benchmark suite for molecular machine learning, which provides various datasets for training AI models in chemical analysis. Explore MoleculeNet on its GitHub repository.

AI and Taste

  • Gastrobots: These are robots designed to taste and analyze food. Researchers have developed AI systems integrated with electronic tongues to evaluate flavors and ingredients in food products.
  • Project “Chefling” by IBM: This project uses AI to generate new recipes and analyze flavor profiles by understanding the chemistry of ingredients and their combinations. More about IBM’s AI initiatives can be found on their research blog.

AI and Smell

  • Digital Olfaction: Companies like Aryballe are developing digital olfactory systems that use AI to identify and classify different smells. These systems have applications in quality control, environmental monitoring, and even in the food and beverage industry. More about Aryballe’s work can be found on their website.
  • Google Brain’s Perfume Project: This initiative focuses on using machine learning to create new fragrances by understanding and predicting how different chemical combinations produce specific scents. More about Google’s AI research can be found on their AI blog.

AI in Pharmaceutical Chemistry

  • Insilico Medicine: This company uses AI for drug discovery and design. It employs deep learning algorithms to predict the effectiveness and potential side effects of new compounds, accelerating the drug development process. Visit their website for more information.
  • BenevolentAI: This project leverages AI to analyze vast amounts of biochemical data to identify new drug candidates and therapeutic targets. Learn more about their projects on their official site.