Tag Archives: Epsilon processor

August 22, 2026 · 16:39

Passing the buck

That is what I saw yesterday, people (I reckon wannabe influencers) are now starting to head towards the setting that AI is the root of all that is evil (apart from that AI being fake, it is not responsible for anything), but as we see the ‘amount’ of so called evidence pile up, you would get this idea. I even saw a reference to one of my own articles (with the wrong data and a reference to another story) added to that pile. So whilst these wannabe’s are not entirely wrong, they are merely adding the wrong quotes to the wrong pile. (They must have used some kind of fake AI). But in the article ‘And Grok ploughed on’ (at https://lawlordtobe.com/2025/11/27/and-grok-ploughed-on/) I made mention on November 27th 2025 “Check out the blog, none of those elements were mentioned there. As some tell us Grok is a generative artificial intelligence (generative AI) chatbot developed by xAI. So where is that AI program now? This is why I made mention in previous blogs that 2026 will be the year that the class actions will start.” And now we see (in various sources “AI-related class action filings are surging in 2026, driven by a sharp rise in investor securities lawsuits over market corrections, ongoing copyright and training data disputes against major tech platforms, and emerging product liability risks” (source: Norton Rose Fulbright) as well as “According to mid-year data from Cornerstone Research and Stanford Law School, federal securities class actions jumped significantly, with 15 AI-related filings recorded in the first half of 2026 alone—nearly matching the 16 total cases filed through the entirety of 2025” (source: CFO Dive). So as I see it, some are passing the buck and whilst there is a shift noticeable in several directions with the premise “Governments are reacting to ongoing friction; for instance, Australia announced intent to establish an Office of AI and legislate stronger artist/creator control over works used in AI training, while courts in the US navigate strict parameters around fair use and dataset destruction” As I see it, the United States wishes their American corporations to get the freedom of fair use (at the expense of anyone else) and others want to keep the IP of the artists and artisans intact. As I am in group two I feel happy that group one might end up with a peppered bill for yours truly (that would be me), but I am not holding my breath on that happening any day soon. And the gremlin in me would love the idea that I gave all my IP to China and see how the USA fights off that setting. I reckon that the Gremlin in me likes that (it will not like to optional fictive loss of revenue, but that is another fight all together).

What is fun is to see these wannabes blame a fictive AI, whilst the users of that fake AI have the larger blame here. But that it also the hidden trap. You see, someone said: “the starting of digital conditions is the beginning of the end. Soon these conditions change and after that the denial that this was ever the case starts” and I tend to agree with this person. We already saw several issues in gaming and a lot more in the business sector and Business Intelligence. The old premise from Emperor Augustus comes calling at that stage “If it isn’t written down, it does not exist” He said so around 25BC, which means that this setting was clear almost 2050 years ago. It seems a hard sell to hear some say “We didn’t think of that” or “It was a corporate policy” and whilst the useless waste more and more of our time, these settings will delve into the framework of too many systems. Which was exactly why I put all my IP online, there are too many settings where things are found out and whilst we accept that, it also means the my chance of financial greatness becomes a little trivial (to say the least). But I still believe that putting in front of everyone is the only way to guarantee your point of view. It is those wannabe’s that state “Just hand it to me, trust me. I’ll do right by you” betting it all on the roulette table is likely the only option for you (even thought the payout is lousy). But in all this I don’t gamble. I even have a setting where otter’s might win some, but the wannabes are likely to never end with one of my dimes.

So whilst we now see that “The Disclosure Dollar Loss Index surged as companies over-promised on AI deployment, infrastructure, and data center capacities, causing sharp stock drops when growth hit roadblocks” (source: Cooley) but here are different roadblocks too. You see, what some claim and what is proven are different settings. We might agree that all AI is bad, but that generalization is also dangerous. Because they could have added a book to their learning curve and whilst the ‘original designer’ forgot that the book in question made the coin tremble, the learning ability might have gotten through this setting in different ways and whilst the Training curve of the fake AI is not explored, because it becomes likely too hard or too convoluted, the mess is created by “All fake AI is evil” and that too is a wrongful generalization that has a deepening effect. So whilst we see ‘over-promised’ the setting is a little sweeter than that. So whilst generalization and wrongful verification comes to blows (which will happened) the investor is left out in the cold and when this happens more than once, the wells dry up fast (which is where I was in 2025, I basically saw this happen in my mind) and in all this verification and validation remains the big two that none of the (fake) AI firms have a handle on. And at present I haven’t seen anyone who is tackling these elements and whilst I still believe that the Epsilon (AI) co processor will optionally solve a lot of issues, there is no way to tell at present. So whilst some call this the Neural Processing Unit (NPU), the settings that current NPU’s and the future Epsilon processor have is a setting that allows trinary data to solve whatever binary cannot do and there is no real time track for that event to happen. Especially when it was decided (years ago) that binary was cheaper and the people behind that brainwave are (speculatively) merely accountants that went the technological setting. They know all about the costs of the setting, but reaping the rewards is also at a low, because they can’t see the benefit that the more expensive solution had and that is where these settings are, but that is merely my speculative view on the drawn stage.

So whilst I see options and benefits, it will likely fall on deaf ears and they are all gong the binary track, which at present is woven and interceded by over a dozen class cases in the first half of this year and at least as much for the second half as well. But we will see how that dollar moves from stage to stage, but regardless of that, even if you consider that the cases at present have settled for over $1.65 billion, how much comes from the investment amounts. How many are purged to be a near total loss? We might think that people like Jeff Bezos, Mark Zuckerberg, Elon Musk and a few others can stand to lose this. But their retirement funds aren’t on the line and those who do will chance to all on some poker bet and risk losing a lot more and these settings should have been sure wins and they were not, this is the trap that no-one wishes to acknowledge that it is in play.

But that is just me, I am not the gambling type and I see too many passing the buck at present and whilst there is a agreeable setting of blaming these fake AI’s the clearer setting is that passing the buck was in the most inconvenient setting. Because if AI is so foolproof, how come that the houses are actively promoting the ’00’ option at these roulette tables? If it was a sure thing, we could all benefit, but the is not the case, is it?

Have a great day this day.

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.

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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Tagged as AI, Alan Woodward, Anthropic, Artificial Intelligence, Binary, ChatGPT, Clement Delangue, Data, data centers, Data farms, DL, DML, Epsilon processor, google, IBM, IP, Katie Moussouris, LISP, LLM, Luta Security, Microsoft, ML, Oracle OpenAI, Surrey University, technology, Trinary, xAI

July 10, 2026 · 22:16

Is it the water level?

Yup, we are all in that setting, but are we merely waving to the music of Debbie Harry or are we watching the waves from the shorelines. That is merely two options, but when some say that the tide is high, they might be referring to bubbles, the AI bubble to be more precise. I am not some economist saying that bubbles are blasphemy and I am no economist, but I have looked at numbers for decades and the numbers we are given do not add up, and when I was watching Inside Job something hit me, there was a familiar pattern evolving, not evolving, repeating is a better word and I have been saying this for some time. Yet today, a mere 10 minutes ago I see ‘UK Places Microsoft, Google, Amazon And Oracle Under Financial Oversight’ (at https://www.businesstoday.com.my/2026/07/10/uk-places-microsoft-google-amazon-and-oracle-under-financial-oversight/) where we see “The UK has placed Microsoft, Google, Amazon and Oracle under direct regulatory oversight after designating the cloud service providers as critical third parties to the country’s financial system. Reuters reported that effective July 13, the designation covers Microsoft Ireland Operations Ltd, Google Cloud EMEA Ltd, Amazon Web Services EMEA SARL and Oracle Corporation UK Ltd, reflecting the financial sector’s growing dependence on cloud infrastructure”, so whilst the story ends with “The designation will bring the four technology firms under direct regulatory oversight as part of efforts to safeguard the stability and continuity of the UK’s financial sector.” And it comes after we were given (at https://m.au.investing.com/news/stock-market-news/oracle-stock-shrugs-off-sp-downgrade-to-bbb-but-120b-debt-shadow-looms-4526441) where we see ‘Oracle stock shrugs off S&P downgrade to ’BBB-’, but $160B debt shadow looms’ where we see “Oracle Corp. (NYSE:ORCL) shares managed to gain 2.7% on Thursday, defying a credit rating downgrade from S&P Global Ratings. While shares edged slightly lower from their midday highs, the tech giant still traded firmly in positive territory. Investors chose to focus on Oracle’s staggering $638 billion backlog of cloud contracts rather than the immediately apparent threat to its balance sheet: S&P downgraded Oracle’s long-term issuer credit rating to ’BBB-’ from ’BBB’, retaining a stable outlook.”

Now, I am not having anything against Oracle. They have always been on the foreground of technology and innovation in its field and it is unlikely to ever change. But there is a larger setting, the entire AI bubble as I see it, it will hit them too. They all over invested in that setting and they are likely the biggest catchers of the implosion of that event. But I am still in arms over ““The official position of the Secretary and the U.S. Treasury is that Artificial intelligence will be a key driver of America’s new Golden Age,” the spokesperson said. “AI has the potential to deliver unprecedented productivity gains, expand economic opportunity, and empower American workers and businesses.”” You see, there is no golden age, there is no AI, not yet at least. There is DML and LLM and they are great, they can hand innovation and prosperity in several ways. It merely isn’ AI and that needs to be said, because soon the class actions will go for the “It’s AI and we cannot really predict what AI does” but it isn’t, it is DML and that requires a programmer, it requires data and these two hinder stones are the backdrop for prosecution. Only last week we were given ‘Anthropic Faces a New $75 Million Lawsuit for Pirating Books to Train Claude AI’ and less than 24 hours ago Harvard Business Review ‘You Outsourced the AI—but you still own the risk’ where we see “As enterprises increasingly embed third-party systems into their workflows, technological risk has led to new legal and operational responsibilities. Leaders may have little visibility into how a model was trained or how it changes, yet when it discriminates, mishandles data, or harms a customer, regulators and plaintiffs often look first to the company that deployed it. Peloton learned how that exposure can arise. Visitors to its website see a familiar invitation to “chat,” powered by a third-party vendor. According to a class-action complaint, the vendor recorded and stored conversations and used the data to improve its machine-learning models. Peloton neither built nor trained the system. Even so, a California federal judge allowed a claim against the company to proceed. The parties later jointly dismissed the case, without publicly disclosing the terms.”

Now consider the amalgamation of these factors (apart from some saying there is no bubble) there is (allegedly) “Worldwide spending on AI is forecast to reach $2.5 trillion. Venture capital and private corporate investments in AI firms sit near $258.7 billion globally, with over $750 billion in dedicated infrastructure and data center capital expenditure from major tech hyperscalers” we then see that the big players (Microsoft, Google, Amazon, Oracle) are basically overextended, facing class actions and all of them are looking at all sorts of financial hardship, because at some stage all these players will be made to rephrase the simple truth that AI is not DML/LLM, it requires more and when the programming is put under a loop that setting comes crashing down. I saw it two years ago that this is the only outcome in some sales people overselling what they had and the simplest setting is not a mere Quantum computer. It requires shallow circuits and what I tend to call The Epsilon processor. True AI cannot exist in a binary setting. The last one is my interpretation of it all and some might disagree. But the Epsilon processor allows for Null, False, True, Both and it is the Both part that makes true AI possible and of course a matching operating systems will be required as well a data carrier and in that case Oracle and Snowflake have the grounds for success. As I see it, all others will fall behind these two.

And last month we were given that “400 newspapers sued OpenAI and Microsoft for scraping their content without permission or compensation to train artificial intelligence programs” even my data has been scraped. So how many will be successful? How many will fail? I have no idea, but the odds are decently stacked against these salespeople. And as the courts rule against these Fake AI bringers (as I see it) there will be a rush of people making a case, all who were sold AI (without clear DML/LLM settings in their contracts) are seeing their pupils transform into dollar signs and they will try to clean house. So when all these settings happen, is the stage for a bubble that far fetched?

I am watching and watching and noting what is due. I reckon that at some point I get the one piece of evidence that will allow me to do just that, 2700 (out of nearly 4000) article scraped seemingly give me an optional case for some dollars (five million plus would be great). And I am not the greediest player in town. So at what point will the investors of $2.5 trillion ring the bell wanting to see payment for their investments? Goldman Sachs gave us last month ‘The AI Investment Boom: When Will It Pay Off?’ With “The economics of artificial intelligence are more questionable today than two years ago, says Goldman Sachs Research’s Jim Covello, as enterprise buyers, model companies, and hyperscalers have yet to show returns on their spend. In a conversation with Alison Nathan and George Lee on Goldman Sachs Exchanges, Covello discusses where we’ve seen economic value accrue to date and why semiconductor companies can’t continue to be the sole beneficiaries of the AI buildout.” As such we see people with serious economic skills worrying and wondering what comes next and I was there at least a year ago. So when will others see the doubt that I am seeing? The money people call the bubble a blasphemy, but they have vested interests. I do not. I merely see the flaws on technology that is at least 15-20 years away, data that is largely unvalidated and unverified and at this juncture people are investing trillions? Makes me all tingly that too many people are greed driven and too much vested to be part of a boom that does not exist, just like the settings of 2008, Inside Job showed that clearly and it seems that we have a similar setting evolve at least two times the previous caper. So if you consider that with all the reserves that hit took the economy 2 decades to fix and at present the reserves are gone, so what will happen now? Why aren’t others taking the stand the UK is making? Because others are in the believe that “America’s new Golden Age” is here? When you realize that it will take close to two decades to arrive, how long until too many investors pull the plug and go somewhere else? What will happen then? That is what I see coming, because at some point more and more people wake up, this is bound to happen, it always does.

So is the water high enough? Have a great day.