Tag Archives: Trinary

August 12, 2026 · 13:20

What to believe?

That is at times the question, because the media is not the most credible one in this world at present. Yet one story made me pause, stop me in my strides at I saw ‘Oracle (NYSE:ORCL) Stock Is Falling Again: Is Its Huge AI Spending Bill Finally Catching Up With It?’ (At https://stocksdownunder.com/oracle-stock-falling-ai-spending-bill/) The story by Ujjwal Maheshwari is certainly plausible, but is it therefor a true setting? I had my question marks in this. You see, he writes a cool yarn (as expressions go) but I have my doubt for my own reasons. I have a few internal speculative settings and mostly they are there as a protective cocoon for Oracle, it is my seeing towards the innovative stages that is set to Larry Ellison, the head honcho behind all these innovations (although most of that work was done by Oracle engineers) so as I see the key points things start to unravel in my brain. Lets go over them.

Oracle stock fell about 4% to around US$144.82 as a recent rebound faded. OK, I have no issues with that, especially as my economic insights tend to be measured per thimble. 

The worry is Oracle’s enormous spending on AI data centres, which has led to negative cash flow and a credit downgrade. Which is one I agree with, but there is an annotation attached to this. Because as I see it, all AI is fake AI, but data is almost forever and the needs to be stored somewhere as I see it, when all this comes into the realm of real AI (sometimes called True AI) it needs data and as I see it Oracle is the one true power to hold all that and even as it needs rewrites, the ones using Oracle will emerge victorious, all whilst others are set to Azure, AWS or whatever Google has, is set to a bind and there is the null moment. Oracle will adjust and attain a new standard of this data, the others are likely to fail (optionally Google might address them too) all others are bound for a shallow grave and whilst I have faith that the IBM hardware will rise to the occasion, I have no idea how their software setting is going to be, I honestly don’t know that part. So as I see it all, Oracle data centres are likely to float above the other muck and that is where the victorious remain. 

So when we get to Oracle plans to spend up to US$95 billion next year building AI infrastructure. Is a price tag I am unsure what to make of, that being said as this AI race comes to a heading those with the proper investments are the only one staying afloat and in that what is to be believed to be  at least US$2.1 trillion in global AI investment commitments are projected through 2027, driven heavily by major tech hyperscalers spending massive capital on data centers. Oracle is likely with its part the only one almost certain to stay afloat and a 95 billion next year against a pool of 2,100 billion is a sturdy island in a sea of turmoil and whilst you see one image, I see a data setting that can adjust and adhere to trinary data centres and that is where Oracle remains alone because that setting was rejected by some and when that happens they will falter because they could not adjust to that setting blowing up the data sizes to almost 500% of what will be a trinary data pool, so it can do it at least 5 times faster on data more ergonomically terrific. That is what I presume will happen, so as I like the writings of Ujjwal Maheshwari, I don’t think he is aware on what is coming that way in less than a decade and that will be the benefit of Oracle and whilst they will get the larger deals others will falter. So what happens when that US$2.1trillion is written off as redundant investments? 

Despite the concerns, most analysts remain bullish, with price targets far above the current level. Is one I am keeping my fingers off. It is like watching an analyst relying on the numbers of a phone book because that is what he believes, all whilst the rest has pushed towards the data sets of tomorrow and there is no real way to see this. Because the phone book is what our parents relied on and it works, but the new directory is not on paper and it is based upon a different scale, with a new price target one that is not seen now and not even speculated on now. As I see it, there analysts are not reset to tomorrow data sets and that is where I need to see what happens. But there is in all likelihood the mother of all reset and I have no idea how these analysts will adjust their settings. We will have to see. 

So whilst I accept the setting we are given “Here is what is happening right now. Today’s drop is less about fresh bad news and more about a recent rebound running out of steam. Oracle’s shares had bounced in recent sessions, and today traders are pulling back again, a common pattern when a stock has fallen out of favour.” But the constant is not the favour that falls, out is the certainty of Oracle as a solution, I know that this doesn’t make much sense, but that I how I see it.  Yes, stocks and options fall in and out of favour, but that doesn’t matter to me, because the technical solution is sound and firm and that doesn’t care about favors. It is like asking market researchers validating actual data of population and that is not done. Data is what it is and adjusting that to data now and data tomorrow matters, not what a market researchers expect it to go to. Confused? I guess that this is what is happening and Oracle is seen as the taste that is out of fashion, but that is the trap, the data is optionally the real deal whether it is now, or if it is new adjusted data and Oracle has always been a master in what it is to what it needs to be and I have no idea if others can adjust to that, I really don’t know. But in that instance I have faith that Oracle will come through. As I see it, Azure and AWS have always been in the mindset of “This is how it needs to be” whilst Oracle “This what data needs to become” optionally Google too (I honestly do not know how flexible they are). One can adjust and others optionally cannot. This is how I see it and that is why I feel that Oracle is the one true dataflexer (a funny reference to what once was). So make of this what you will and of course you could massively disagree, your right but if it is your investment, you lose. That is the big numbers game and investor have given their voice to US$2.1 trillion and at a dollar per voice the adjustment shock will kill plenty of people in that race. 

So it doesn’t matter that I consider all AI to be fake AI, it is still about the attached data and when that is real and stable, things will adjust for the better. And as I see it, you better have a proper adjustable data set. Have a great day today.

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August 11, 2026 · 20:24

Is Grok losing the plot?

That is the actual setting and it takes a little space to explain this part. So the other day I was ‘watching’ Elon Musk giving us the following explanation: “Elon Musk predicts that artificial intelligence will exceed the sum of all human intelligence by around 2031, leading to a profound transformation where digital work is automated rapidly, human control shifts within a decade, and ubiquitous robotics trigger an unprecedented global economic boom” and some might say that at $1,000,000,000,000 he is likely nothing more than a 2nd hands car salesman (a very well paid one), I actually don’t care, because all AI is fake AI and yesterday I got some evidence on all this. 

So, why get Elon involved? Well, he owns Grok and Grok was the setting of it all. You see, I tend to pass my articles through Grok. In part for the entertainment, in part to see if Grok saw what I was seeing and at times to see what it sees more. So what happened? It started with my article ‘Flame on’ (at https://lawlordtobe.com/2026/08/09/flame-on/) nothing special, but Grok ‘devaluated’ this to:

The X post from @lawrencevanrijn on August 9, 2026, consists solely of a link to his blog post titled “Flame on” on lawlordtobe.com with no accompanying text or commentary.
The linked WordPress article features the title “Flame on | Lawrence van Rijn – Law Lord to be” but contains no substantive body text, headings, or visible content beyond standard site elements like comment sections and navigation.
Consistent with the author’s IT and IP law background, “Flame on” likely serves as a metaphorical title possibly referencing internet flaming jargon or igniting discussion, though the post currently appears incomplete or placeholder-like.

Read the story and you start seeing the issue. I also passed this through ChatGPT (my very first visit) and that gave a little bit tedious, but a real good assessment, attacking the article on what it saw (whilst it ignored the setting that it was a blog and not an academic paper). As it was (fake) AI I tried regenerating the output, but it was all useless and even less useful than what you read above. I tried Google Gemini, but that one doesn’t seemingly accept an internet link (I might not have used it correctly) but the simple setting is that Grok might have been losing the plot. So I used it two subsequent days and it all looks decent, so I tried it again onboard ‘Flame on’ and again a failure. 

So now we get to the insanity setting that doing the same thing and expecting different results might be insane. But as I see it, this is all DML (Deeper Machine Language) and LLM (Large Language Models) in action and there is enough setting to optionally expect a different result. There is also the seating that all this is programming and not AI. As such errors are fixed and more changes are made making this an optional never a static setting. So whilst I would love to blame the programmer (and it likely is) there is a setting we cannot ignore and in the past I have seen that Grok does not align to multiple viewpoints correctly (and I have 4 examples somewhere to show it cannot decently do this). So whilst we agree that this is not a complex setting, it is programming, pure and simple.

I have seen my share of lever programming and whilst we can agree that LLM settings are getting clever, it is not AI, nor will it ever be (as I have stated a few times in the past). So whilst I applaud ChatGPT on the ability to ant-fuck the equation (a Dutch expression), it is clever, optionally wholesome, but not AI. So whilst we now see that too many people are buying into the AI setting and even accepting that it can go rogue and hack settings, all whilst it is programmer controlled, as such, these players are likely adhering to state players and all this is needed to gan the insights of corporate IP and seeing how they could turn a dime. This and this alone is why I pushed all my IP to public domain and as I would never gain coins from any of this, I made it public domain, so that the right people have something to work on. My legacy to leave the world.

So is Grok losing the plot? It is a fair question and whilst Grok could not analyze my piece and ChatGPT could, there is a clear setting that this is optionally the case. It does not matter that it only failed once. If it was an AI, it should not ever fail once. That is the reality of a real AI. It gets it right 100% of the time of there is data and my article is data. It is when there is no data that an actual AI gets it right over 98% of the time and that is not happening either in many cases, as such I call all AI fake AI.

That is the setting and whilst some will debate this (and disagree) there is plenty of evidence around to say that I am right, A stage we cannot ignore and whilst some (optionally correct) disagree that Grok has not lost the plot, the seating is out there and the evidence is all out there. And these ‘captains of industry’ have to agree that their solutions is riddled with issues (as they are programmed) or that they are invoking the AI label to get away with whatever they can. So whilst some might agree with the setting of “exceed the sum of all human intelligence by around 2031”, it is a setting that I disagree with, because having all the data of every book and every encyclopedia is nice, but it is merely clever LLM programming. Exceeding the sum of human intelligence requires to make correct leaps of non data, extrapolation of non existing data (like speculation and presumption) and these systems still aren’t able to do that and I wrote about it in the past and it will require an optional 2 decades to do that and that exceeds the timing point of Elon Musk by well over a decade and personally I believe that it will not even be correctly possible without an Epsilon processor (a speculative trinary processor) because the setting of Null, True, False will only incur additional and more errors making ‘their’ setting of AI less and less reliable and that is before we validate and verify the data these systems have and they haven’t worked that out yet. As I see it the first step is getting the Epsilon processor online which will give us the option of Null, True, False, Both. That is a first step and none of these systems have that, because the processor doesn’t exist yet (perhaps the Dutch physicist is on route, but I have no idea where they are). So in all this we might get more and more of systems losing the plot and that is whilst they have all the data and my article is less then 3000 characters. Consider that when you consider these AI systems being clever. 

So have a great day and perhaps I have more (optionally) sneaky stuff too hand you in under 20 hours. 

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July 25, 2026 · 22:45

Rerun anyone?

As I wrote an article propping questions there. I see earlier today, the BBC is giving us ‘Warning shot or publicity stunt – how worried should we be about the OpenAI hack?’ (at https://www.bbc.com/news/articles/cd9w22n9e4go) as such, I had some initial questions in my article: ‘Is it real or is it media?’ (at https://lawlordtobe.com/2026/07/24/is-it-real-or-is-it-media/) where I posted the idea ““The ChatGPT-maker said its agent – an AI system which can operate alone after human instruction – was being tested in a controlled environment but, after finding weaknesses, was able to escape the test limits.” Which is fine, but that is still programmer controlled. So as I see it “after finding weaknesses, was able to escape the test limits” it didn’t escape it merely found a weakness as its ML systems were taught to find out and went elsewhere. It reminded my of the 90s hacking setting where towards ‘password’ a clever hacker gave “1=1” invoking the ‘True’ setting. Then we get “OpenAI said the incident was “unprecedented”, and it was conducting an investigation alongside Hugging Face, whose boss Clement Delangue said in a post on X it was “mind-blowing that all of this happened autonomously”.”” And now we see “Hugging Face said the hack was different from anything it had handled before because it was done at superhuman speed by an AI with little or no human guidance.” It is the “little” addition to the sentence that is validating my setting of “that is still programmer controlled”, because as I see it, “little guidance” might merely be human ‘adjusting’. And when we see “Hugging Face researchers guessed the mysterious attackers had used one of the big AI models but they had no idea who or where the criminals were.” So, the issues is even bigger, it could have been Organized Crime setting the parameters of a sandbox, I know it sounds outlandish, but there is either a massive shortage in structure and security of DML (Deeper Machine Learning) settings (so it could either be ML or DL) but the setting that this is out there whilst there is no oversight is something that most of the media is painting over with innuendo and whether this is given by some is not in question, also irrelevant. And we see this when we get to “The Scooby-Doo-style reveal was made even more bizarre – and worrying – because OpenAI said its bot did the whole thing on its own, without permission. The firm said it all went down during a test of its tech’s hacking skills.

Two new versions of ChatGPT, designed to be master hackers, broke out of a supposedly secure test environment and gained access to the internet.” We see “broke out of a supposedly secure test environment” implies that it was not secure and the testing facility (the sandbox) is lacking security and oversight. And the statement “OpenAI said its bot did the whole thing on its own” implies that the bot was not monitored or ‘left alone in limbo’ but we all know that any computer is  never idle, it is always doing something and whilst it depends on human interactions it is fine. With autonomous systems it is a different matter and OpenAI should have known that. They are supposed whole lot better than I would ever be and I reckon that the larger issue is what did OpenAI know ad what are they hiding, because as I see it, they are hiding something. I am not sure what and it might be innocent in most cases but as I see it, hiding something is fear for some illumination. That has for themes nearly always been the case.

Then the BBC hits a note that I was playing all along a for the most I hinted to that in the previous article (listed above) but the BBC is giving us “Was it truly a stark warning about the future of AI? Or was it a publicity stunt by OpenAI to show off how powerful their models are? It’s the kind of scare marketing AI companies have been accused of for years and, since the much discussed launch of Anthropic’s Mythos model, cyber-security prowess has been a focal point. One of the top comments on OpenAI boss Sam Altman’s X post about the incident summarises this skepticism: “If y’all can’t understand that this was written to purely brag about the model then I don’t know what to tell you.”” And the ‘statement’ “If y’all can’t understand that this was written to purely brag about the model then I don’t know what to tell you” summarizes it nicely. We also get “The OpenAI and Hugging Face incident is a real-world example of a broader issue we’ve been highlighting for months,” said Dor Sarig from Pillar Security. “Sandboxes alone are not a sufficient security boundary for agentic AI.” And I tend to agree with that. Any Agentic system requires different security requirements. Whether it is Fake AI, True AI or simple ML AI. An agentic system does not work according to ‘human’ settings. I tend to go back to the original chess computers from the 80s. They will try any movement that is possible until they get the right result whilst replaying every chess match that was programmed into its memory. And the chess computer is relatively simple. Hacking into a system has all kind of places to pass. I gave the window example in my previous article. But the setting of software is that they are set to libraries that give abilities to a program. You see, a program gets linked to <stdio.h>, <stdlib.h> and <string.h>, but merely these three open up options in I/O operations, copy operations that are not part of the program, but they are in that system and it can run by all of them in mere seconds, optionally finding alternative options. Even this is not AI, a programmer had to program it in and regardless whether an agentic system does it autonomously, it only does it because it was handed that training and these instructions, and the agentic system started to combine options and learnings and it learned (using my previous examples) that it can leave a location via a window, it does not require to use a door. Which makes me remember an MSDOS program that turned the speaker into a device. So giving it the instruction:

Copy MontyPython SPKR:
Copy MontyPython SPKR:
Copy MontyPython SPKR:
Copy MontyPython SPKR:
Copy MontyPython SPKR:

And then wait from a distance, whist I added this to the autoexec.bat of a friend and watch him go nuts why his PC is singing the tune of Monty Python. It wasn’t me, someone programmed the setting of a speaker to become a SPKR: drive. So when an agentic program gets creative it might take routes no programmer could anticipate, not even when he/she programmed it. Because the reality of the setting is that no sandbox suffices to any agentic program. As I see it, it requires a sandbox in a sandbox and when the agentic program gets out of the inner sandbox the arms of the outer sandbox go off and as I see it, because it was unmentioned, that setting seemingly does not exist.  So whilst I understand the position given by “Cyber security Professor Alan Woodward from Surrey University told reporters OpenAI had “egg on it’s face”, and Katie Moussouris from Luta Security went further, suggesting the AI industry is failing to control its dangerous inventions.” I kinda disagree and it comes from the plain setting that AI does not yet exist. And all this is the consequence of ‘experts’ covering each other by making claims that all this is AI, whilst it is mere ML/DL (I call it DML) and it comes from a programmer. And even as they are covering each other, and clapping each other on the back. They know that the wrong settings are in place, but they are in too deep and it will hinder whatever comes next. There is one upside, you see, the AI Kill Switch Act might be in place before True AI comes to town and that could be the one great good thing.

I get the doubt thrown my way and I get that a lot of people have no idea, even though they gave all their IP and data to ChatGPT. I never used it and until there is a real AI, I will never use it to grow ideas. So whilst IBM (decently recent) gave us “Key concerns include autonomous system risks, data privacy violations, algorithmic bias, widespread misinformation, and intellectual property challenges” which is something I gave several times in the past and it all comes from a programmer, and as soon as they get connected to some sort of organized criminal enterprise the fence is broken open and all that IP will go anywhere and everywhere. That is the larger setting and no one is examining the ML/DL libraries that these players are making and as such when these class actions are placed beyond the settlements that they can afford, the ‘sudden’ revelation comes out and that is the moment these programmers can’t remember anything. And whilst the setting comes to point that the dollar sign no longer validates the setting of “Tech companies argue that training AI on public data falls under legal “fair use,” while creators argue it is unauthorized commercial exploitation” we will get a whole new ballgame and whilst this all plays out, the tech companies are creating new libraries with these agentic knowledge basis making a secure sandbox even more difficult. Optionally it might even contain three sandboxes in a nested structure, but that is merely my view on the matter and I might be incorrect in that assessment. 

So whilst we are facing rerun after rerun and optionally faked settings of Google vs OpenAI, both against Anthropic and all against each other when xAI enters the fold. And all that time the are still figuring out both a Trinary system (I see that as an essential setting for True AI) and how that is voiced into data systems, because they will have ramifications. Which is why I see that Oracle and Snowflake have the largest chances in that respect. I am certain that this is a race that Microsoft is unable to get into and I have no idea where Google is there. I am decently certain that IBM figured this out before I did and optionally they have this ‘under control’ through what was LISP and is now optionally coming to systems in some point in the future. Because as I see it, the setting of a trinary driven system with what I tend to call an Epsilon processor would require a LISP driven setting where the optional inclusion and exclusion would run simultaneously and this requires some form of LISP setting (a personal speculation) and all this would come with IBM shallow circuits. And all this gives IBM the largest head start, even Google might not be able to compete and I reckon that IBM might have talked to someone like Oracle on these settings. I have no idea where IBM is in databases, because in the end any true AI system is depending on the data it has. The question becomes in the meantime, how to transform binary (fake) AI into trinity true AI. The setting will become the discussion among data experts in the next few years and it hold bearing to all this, because it also impacts on how sandboxes are designed and monitored. 

And it it important because as I see it, trinary data takes a fifth of the space whilst gaining 4 times the speed of processing. And that is the setting these data farms will have to content with. As such there is plenty of evolution coming, but in this the stages of security becomes essential and whilst you consider rate quote from Katie Moussouris from Luta Security giving us “the AI industry is failing to control its dangerous inventions” and we are nowhere near the setting of true AI and that is where sandboxes require a nasty upgrade and soon, because soon enough, the kill switch might all there is between our data and whomever has access to data farms. And with security failing like we see now, we might not have that much time left and that is where I saw the need for security, because there is every chance that some AI ‘dealers’ already know that their fortune is set towards who has the most data and there is a need that we need to keep our data safe, but others might not want to do anything about it. Naming names is highly speculative because we aren’t shown the real issues and these people don’t want the real issues to come out because when the game is up, these people are playing for all the marbles in the world and there can only be one winner. That is how I see it and I might be wrong, but at present I feel that I am more right than even I think I should be. 

Have a great day today, I am now a mere 80 minutes away from Sunday.

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May 17, 2026 · 10:05

In my mind

This is not some setting from “because I say so”, but it is a setting that I expect. To see what trinary systems (some call them ternary systems) can do ‘because of’ “Potentially higher speed and efficiency, allowing for less storage space per bit and more compact circuitry. Balanced ternary handles negative numbers natively.” The IT world is relying on the setting (because it knocks them of their throne) with “Difficult to design, higher power consumption in some implementations, and a lack of mature research compared to binary.” They are not wrong, but trinary is tomorrow and it is set to actual and factual true Artificial Intelligence. As such in my mind the system created 1,000,000 possible culprits, but the setting to identify this (with much in the middle of the data) we see a cube with a 100 layers of 100 by 100 people. Each person has over 100 elements and that is still a decent data setting. The binary solution gives us 4 reds (highly likely culprits), two dozen orange (people who are not to be dismissed as a suspect at present) and the rest is cleared, it took the binary solution 47 seconds. So in comes the trinary solution and it gives us two reds and 5 orange and it does so in 6 seconds. That is the setting that trinary beers binary gives us on 1,000,000 people. So when (lets for arguments sake say Oracle) gives the people the impact of that and the gain in computational power as well as offer higher information density and theoretical efficiency. The sales talk is done at that point and consider the amounts of data sources have, we can say that at that point Binary solutions are done for in a world where time matters and where efficiency is goal. You should not dismiss Fake AI that easily, because some people cannot afford trinary solutions before 2040-2050. But that setting if computational power is not to be dismissed. No matter what the binary tycoons claim. So in 6 seconds, the 19 non-dismissible people were disregarded on the foundation of the SAME data, because that was part of the exercise. And I reckon that shallow circuits will be a much stronger solution in a trinary setting that it ever could be in a binary setting. Don’t get me wrong, it will help heaps. 1 million people with over 100 elements is still 100,000,000 settings in a true/false environment. This is why I disregard (at present) as all AI, simply as fake AI. And for the people stating this is merely in my mind. You are right and fortunately I had an education from UTS and a degree in internet working. So we all have had that setting of data and non-repudiation. And don’t forget in a trinary setting non-repudiation is more than a simple equation. It will figure out that you and only you could have done something like that. This is why I valued Oracle (and optionally Snowflake) above all the others, by the time you are done with listening to the salespeople from Azure stating that this is the way to go, you are hooked and that is where you lose the fight. And when Oracle set up whatever they call there trinary database system, there will be a population of one in the forefront of real AI and those who were ‘enticed’ by the sales talk of others, because those salespeople don’t care about you, they care about their own product and they are set to do the best that their solution can do for you. Here language and legal settings matter, because they never outspokenly lie, they merely omit factors that they regard don’t concern you. Even Google Gemini give us “ternary remains limited by manufacturing complexity and lower reliability.” Every one who knows me knows that I am a huge Google fan, so where did Gemini gets that data? (simple: reddit) and it gives the source, but how was it verified and validated? And at present it is a true setting, but if you realise that this technology is still well over a decade away (at best) are they lying? You need to see the bigger picture, especially when these vendors trow phrases like “AI” around and when people are cluing up that it is all Fake AI, we will see carefully phrased denials like “they were all doing it, we just followed them” and that is where you see that these proclaimers are merely following one another. What a tangled web we weave. 

Still I reckon that Snowflake and Oracle will have transference systems in development, because I am not the ‘genius of one innovator’ others have similar setting in mind and they are preparing to give their customers the best that is possible with the current technology in place. 

So as we are looking at a day of rest (or like me slaughtering people in Skyrim), we need to consider the media frenzy that is evolving around us and be very careful what you accept as true. Even my statements should be examined. The one stating “My data is without flaw” is the liar in your inner circle. And be careful who you let into your inner circle because that is your decision and it will cost you the moment you allow the wrong person in your midst. 

Have a great day. So don’t think of this ‘article or story’ as valid, it is a collection of thoughts that are mine and even as I presume that it is all factual, it remains a story unless I can verify and validate the data I have and some of this was collected through fake AI, so I know there are parts that are not aligning. 

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November 6, 2025 · 16:38

Ignoring the centre of the pie

That is the setting that I saw when I took notice of ‘Will quantum be bigger than AI?’ (at https://www.bbc.com/news/articles/c04gvx7egw5o) now there is no real blame to show here. There is no blame on Zoe Kleinman (she is an editor). As I personally see it, we have no AI. What we have is DML and LLM (and combinations of the two), they are great and great tools and they can get a whole lot done, but it is not AI. Why do I feel this way? The only real version of AI was the one Alan Turing introduced us to and we are not there yet. Three components are missing. The first is Quantum Processing. We have that, but it is still in its infancy. The few true Quantum systems there are are in the hands of Google, IBM and I reckon Microsoft. I have no idea who leads this field but these are the players. Still they need a few things. In the first setting Shallow Circuits needs to be evolved. As far as I know (which is not much) is that it is still evolving. So what is a shallow circuit. Well, you have a number of steps to degrade the process. The larger the process, the larger the steps. Shallow circuits makes this easier. To put it in layman’s terms. The process doesn’t grow, it is simplified. 

To put this in perspective, lets take another look. In the 90’s we had Btree+ trees. In that setting, lets say we have a register with a million entries. In Btree it goes to the 50% marker, was the record we needed further or less than that. Then it takes half go that and does the same query. So as one system (like DBase3+ goes from start to finish), Btree goes 0 to 500,000 to 750,000 to 625,000. As such in 4 steps it passed through 624999 records. This is the speediest setting and it is not foolproof, that record setting is a monster to maintain, but it had benefits. Shallow Circuits has roughly the same benefits (if you want to read up to this, there is something at https://qutech.nl/wp-content/uploads/2018/02/m1-koenig.pdf) it was a collaboration of Robert König with Sergey Bravyi and David Gosset in 2018. And the gist of it is given through “Many locality constraints on 2D HLF-solving circuits” where “A classical circuit which solves the 2D HLF must satisfy all such cycle relations” and the stage becomes “We show that constant-depth locality is incompatible with these constraints” and now you get the first setting that these AI’s we see out there aren’t real AI’s and that will be the start of several class actions in 2026 (as I personally see it) and as far as I can tell, large law firms are suiting up for this as these are potentially trillion dollar money makers (see this as 5 times $200B) as such law firms are on board, for defense and for prosecution, you see, there is another step missing, two steps actually. The first is that this requires a new operating system, one that enables the use of the Epsilon Particle. You see, it will be the end of Binary computation and the beginning of Trinary computations which are essential to True AI (I am adopting this phrase to stop confusion) You see, the world is no really Yes/No (or True/False), that is not how True AI or nature works. We merely adopted this setting decades ago, because that was what there was and IBM got us there. You see, there is one step missing and it is seen in the setting NULL,TRUE,FALSE,BOTH. NULL is that there are no interactions, the action is FALSE, TRUE or BOTH, that is a valid setting and the people who claim bravely (might be stupidly) that they can do this are the first to fall into these losing class actions. The quantum chip can deal with the premise, but the OS it deals with needs to have a trinary setting to deal with the BOTH option and that is where the horse is currently absent. As I see it, that stage is likely a decade away (but I could be wrong and I have no idea where IBM is in that setting as the paper is almost a decade old. 

But that is the setting I see, so when we go back to the BBC with “AI’s value is forecast in the trillions. But they both live under the shadow of hype and the bursting of bubbles. “I used to believe that quantum computing was the most-hyped technology until the AI craze emerged,” jokes Mr Hopkins.” Fair view, but as I see it the AI bible is a real bubble with all the dangers it holds as AI isn’t real (at present), Quantum is a real deal and only a few can afford it (hence IBM, Google, Microsoft) and the people who can afford such a system (apart from these companies) are Mark Zuckerberg, Elon Musk, Sergei Brin and Larry Ellison (as far as I know) because a real quantum computer takes up a truckload of energy and the processor (and storage are massively expensive, how expensive? Well I don’t think Aramco could afford it, now without dropping a few projects along the way. So you need to be THAT rich to say the least. To give another frame of reference “Google unveiled a new quantum chip called Willow, which it claimed could take five minutes to solve a problem that would currently take the world’s fastest super computers 10 septillion years – or 10,000,000,000,000,000,000,000,000 years – to complete.” And that is the setting for True AI, but in this the programming isn’t even close to ready, because this is all problem by problem all whilst a True AI (like V.I.K.I. in I Robot) can juggle all these problems in an instant. As I personally see it, that setting is decades away and that is if the previous steps are dealt with. Even as I oppose the thought “Analysts warned some key quantum stocks could fall by up to 62%” as there is nothing wrong with Quantum computing, as I see its it is the expectations of the shareholders who are likely wrong. Quantum is solid, but it is a niche without a paddock. Still, whomever holds the Quantum reigns will be the first one to hold a true AI and that is worth the worries and the profits that follow. 

So as I see this article as an eye opener, I don’t really see eye to eye on this side. The writer did nothing wrong. So whilst we might see that Elon Musk was right stating “This week Elon Musk suggested on X that quantum computing would run best on the “permanently shadowed craters of the moon”.” That might work with super magnet drives, quantum locking and a few other settings on the edge of the dark side of the moon, I see some ‘play’ on this, but I have no idea how far this is set and what the data storage systems are (at present) and that is the larger equation here. Because as I see it, trinary data can not be stored on binary data carriers, no matter who cool it is with liquid nitrogen. And that is at the centre of the pie. How to store it all because like the energy constraints, the processing constraints, the tech firms did not really elaborate on this, did they? So how far that is is anyones guess, but I personally would consider (at present, and uneducated) that IBM to be the ruling king of the storage systems. But that might be wrong.

So have a great day and consider where your money is, because when these class actions hit, someone wins and it is most likely the lawyer that collects the fees, the rest will lose just like any other player in that town. So how do you like your coffee at present and do you want a normal cup or a quantum thermal?

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