Tag Archives: Artificial Intelligence

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.

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August 16, 2026 · 03:22

Wolves or Chihuahuas?

I am acting on a feeling, this happens. But the difference is that I have no economic sense (not really), It comes to a ground setting that I can get rich because I spend ;less than I earn, but not fast enough to use tax benefits as leverage to make a larger offset. I don’t know the laws on this and it doesn’t worry me. But I know data, I’ve seen it rustle for the better part of half a century and I noticed today that things are off. I have written about Oracle before, the last time just a day ago. But something seems to have changed. I wrote about vulture investors, but there that is 2-3 years away. And now I see that Oracle is at the centre of way too much press and it is diverse. It is like seeing the set up of a play that some are making and they need to press to do some of the waves and groundwork. That is what I feel, but am I right? The last one (that I think I saw) was ‘Alphabet vs. Oracle: Which Is the Better AI Stock to Own for the Next 5 Years?’ (Yahoo Finance), the article is seemingly nice, but there is an undertone in all this. First of all, why even make the comparison? They have overlapping settings in different directions and I get that you have to make a choice, but that tends to be a personal one. I am such a coward that I would try to go 50-50 on them, they are both sound good and they make an excellent setting for my portfolio. Then we also get ‘Oracle Heavily Shorted, Stock Halved—Contrarian Opportunity?’ And ‘Oracle’s $10,000 Lesson: A 38% Plunge in 12 Months Despite Record AI Backlog’ followed by ‘Oracle Stock Falls 3.8% as $40 Billion Funding Plan Tests AI Backlog’ and ‘Project Jupiter: Gas Pipeline Delay Threatens Oracle’s $165 Billion New Mexico AI Data Center’ (less than an hour ago) as I see it, it started with ‘Oracle junk bond fears, debt surge sound alarms for investors’ 23 hours ago. There are always setting that happen at the same time, but to see 6 pages of headlines in the last 24 hours and diverse, it is not that they all talk about 1 thing. It comes across that the attacks on Oracle are beginning and everyone wants to take a bite out of that data behemoth. That is what it feels like to me, someone is gunning for Oracle and I have no idea who, but someone knows. 

The problem for me is that it sounds like the wolves are coming and they might merely be chihuahuas making noises. The setting is that I am not economically savvy enough to make the distinction (I am no Mark Carney after all), but the data that I see gives me the feeling that they are wolves setting up for a yummy clambake and they are setting the table. This is the groundwork I expected to see starting around December 2027, not in the last 24 hours. I get that someone will make the point that the world never sleeps and that business is always on the menu, I get that, but to start carving into a behemoth like this, before that ‘carcass’ is well and ready means that some are showing their hands and whilst this might be a prelude to an actual attack, which means that someone is seeing the soft spot at Oracle, but is that really the case? I lack the economic savvy that I need for this. I can see the data, but that still leaves for a lot of time, these steps give me that Oracle is out of time, or at least that is the premise I notice and that is the problem. Are these chihuahuas that want to make nose to get noticed or are the wolves famished and they need (read: desire) a proper non vegetarian meal? I it just the distance that I fail to see, or is it the noise I hear and I cannot tell the difference? That is the lack of economy in me and I get that, but the data, the data is out there and I surely hope that they are merely chihuahuas, Oracle can stomp on them and shoo them towards a long walk on a short pier, but in the other case, is are we watching the prelude to boardroom tables setting up a circle setting to fight off the wolves? My data insight tells me it is too soon for that, but it requires economic savvy to tell that difference. The data is not there and whilst Oracle has a lot more data insight then I do (never be afraid to honor the biggest dog in the game), I feel that there is rustling in the shrubberies and it is time to differentiate between chihuahuas and wolves. It is not a simple difference because you top on one and shooting of the others (the rest will take a step back). One is a simple miscommunication the other  requires a license, even if it is self defence, so as I see it Oracle better get ready for whatever they plan.

The question is, what do you do when the wolves come calling early? Have a great Sunday, not in Toronto and Vancouver though, for them it is still Caturday and they are hugging their tigers (as men do).

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August 15, 2026 · 00:48

Worries

That is what I felt. Computing, a media brand of The Channel Company, is a trusted source for end-user IT news, analysis and insight around the world gave me news that gave me a few thoughts. The article ‘Oracle plans more job cuts as AI bill rises’ left me with worries. If this is the setting for Oracle, what more can go bust in the night? I personally don’t care about these grocery stores like Microsoft, they made their own bed. But “An internal document seen by Business Insider says some teams could see double-digit percentage reductions in their workforce. Managers have reportedly been asked to identify employees whose jobs could be cut, with the aim of reducing payroll by the start of Oracle’s second quarter on 1st September.” Gives me pause for worries. You see, I have worked a lifetime on technical support and customer care and I have always had my worries about this entire spending against these rising “AI bills”, first of all AI doesn’t exist. No matter what you call it, it is not AI, it is mere DML/LLM settings and they are part of an AI, but it is not AI and whilst everyone is spending the house, the fireplace and the kitchen sink, it is a moot setting. It is seen in the fact that AI (now called true AI) is over a decade away and how many firms will remain as they are all hollowing out into what some call an empty egg shell? I for one had the most hope towards IBM and Oracle, IBM is the closest in hardware (the entire Quantum processor, shallow circuits) settings, and merely (as I personally see it) a lacking trinary operating system and what I call an Epsilon processor, like the old days had an Coprocessor (like the 80387, a dedicated hardware math coprocessor) and in my mind the Epsilon processor will be the AI (co)processor, dealing with trinary data settings. It might not be the correct setting, but this is what I personally believe. As such I still believe we are close to two decades away from all of this, but there is no way that these spending can go on for another 2-3 years. These firms are destined to lose whatever advantage they had and are ready to be fed to vulture investors, aggressive financiers who buy distressed assets and as I see it, Oracle, Microsoft, AWS and several others will become massively distressed in 2-3 years, especially as they are hollowing out their company. It is my personal believe that these vulture investors are chipping at the bits to take control of these firm. Especially when you see “Oracle’s workforce fell by about 21,000 people, or 13%, during its financial year ending on 31st May, according to a recent company filing. The company currently employs about 141,000 people.” Consider what Oracle brings to the table, how many people could they sacrifice before the lid of that box becomes too shaky to survive? I have no idea, because I am not in the know about Oracle, I know people there, but that is as far as it goes. So when I read “Oracle said the deployment of AI technologies across its operations had already resulted in reductions to its workforce and could lead to further cuts.” As well as “Oracle is investing heavily to expand its cloud infrastructure as demand for computing power used to develop and run AI systems surges. Its capital spending reached about $55.7 billion in the 2026 financial year, up sharply from $21.2 billion a year earlier, as it accelerated construction of datacentres and purchases of equipment. The scale of that investment has increased pressure on the company’s finances. Oracle recorded an operating cash shortfall of about $23.7 billion during the year and raised roughly $43 billion through debt. It is also expected to raise a further $40 billion, alongside about $5 billion in equity.” This leads us to “S&P Global Ratings cut Oracle’s long-term credit rating to BBB-, one level above junk status, citing rising debt and sharply negative cash flow. Despite the financial pressure, Oracle’s latest results showed strong demand. Revenue increased by 17% in its latest financial year, while its cloud infrastructure business grew by 77%. The company’s chairman, Larry Ellison, has previously played down concerns that AI could undermine established software firms, saying the so-called “SaaSpocalypse” would be a problem for other companies rather than Oracle.” I am the last one to spell doom over any company (except Microsoft), but these settings leaves doubts over the future of Oracle. And there is the setting that I could be wrong with the trinary approach and my feelings on the matter are fluidic at best, but in that setting IBM has the highest chance of success, and I believe that it will happen with Oracle data. But that is my personal feelings in the matter. Still the article in  Computing (at https://www.computing.co.uk/news/2026/ai/oracle-plans-more-job-cuts-as-ai-bill-rises) leaves me with worries for Oracle, if 13% was already made redundant and another 11% might come, what happens when almost 25% is gone? What happens to training, support, services? I reckon that the sales people are all in it for themselves (as commercially driven entities are) but at some point they see that this cannot continue and as I see it, it will leave a place like Oracle at the mercy of vulture investors. 

I understand I could be wrong in a few ways, but consider what AI is supposed to be and it is not. We see all these ‘BS directives of expert AI’ that got lose (all whilst there is no real AI), it hacked its way into place X and out of sandbox Y, which I see as evidence that it is not really AI, it is a Machine Learning application (with optional LLM) that is programmed and that is what some are hiding, because all these class actions will suddenly have new fuel, programmers will be shown to the media, telling the world what they programmed and these firms, none of them will survive the costs of these cases. Some give us numbers that indicate that AI-related investor fraud and disclosure lawsuits spiked sharply, accounting for over $385 billion in measured Disclosure Dollar Losses in early 2026 alone, driving massive defense and litigation overhead and as far as I can tell the total costs for 2026 gets to surpass $400 billion, now consider that the ‘gig is up’ as some say and the class actions will rise to new heights. I predicted as such a few times, going back to February 19th 2026, and as I see it, there is more to come and these firms will be protective of whatever their coffers have, because at this pace, their revenue will collapse when some settings come to pass and they have hollowed out their companies. They did it themselves and whilst I don’t know the specifics, I saw this as a really bad idea, no matter what the influx tended to be, I served in customer care and technical support going all the way back to 1985, I have seen it all before and when these companies short change on training, support, and services it tends to go downhill fast. But that might merely be me. So how to see this article? I reckon that it is a wake up call. I am not of the mind that I am changing my mind about certain matters, but I am weary that there is a larger danger ahead of us all and it is the dangers of weakened firms now becoming the target of vulture investors within the next 3 years. Will it happen? I have no idea and I didn’t think of these vulture investors initially, but that is the first weakness that these firms face when they weaken themselves to this degree. Will it happen? I guess so as greed goes where payments are found and most of us enabled it. We did so by ‘heralding’ “The current “golden age of AI” refers to the mid-2020s boom driven by generative models, multimodal transformers, and massive computational scaling that has transformed enterprise productivity, robotics, and creative industries.” So you tell me, what golden age? Doesn’t such a golden age come with large revenues all over the board? So far we are drowned by articles on class actions, costings that make firms get rid of thousands of workers. What golden age I ask you.

So, this article is highly speculative, I get that but is it therefor wrong and not happening? Too much of these events are now becoming fact, except the revenue from AI, that is still illusive all over the board. Except for a few companies but they are paying each other for data centres, so is it really revenue or an exercise in funny money. Have a great day today.

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August 13, 2026 · 10:50

Today’s village idiot

There is a setting I have kept my eyes on, because I have had more than one issue and it is time to be the not so nice person. So whilst we see LinkedIn giving us:

The ‘small’ fact that two people checked me out. The reality is that the profile viewers, the ones we are given 

Give us that a minimum of three were there in the last day, I know for a fact that at least two additional people locked at me in the two days preceding that and I know for a fact that at least 2 more watched me, but I have no idea who they were. That gives us the following setting (because LinkedIn is part of Microsoft) It implies (using pig calculus) that LinkedIn is only 22.2%-28.5% precise and the setting is that they are even not that accurate. So are you willing to give your data and hard earned IP to a setting where they are at best 28.5% accurate? How will that go for you, your company data and a lot more. And the art of tally has been around for over 5000 years, some people might have explained that to their village idiot in 1095 (when the poor got ‘drafted’ by the local ‘faithful’ for the Crusades). And these idiots are optionally better tallyman than LinkedIn/Microsoft? Go cry me a river, please.

So whilst we are given (from diverse sources) “Inflated Applicant Numbers: The “X applicants” number shown on job listings tracks how many people clicked the Apply button, not how many actually finished or submitted an application.” As well as “Algorithmic Hype: The feed often rewards “flex culture” and exaggerated success stories, making normal career struggles feel abnormal or invisible.” (Source: Google) 

I am speculating that there is method to their insanity. The United States is eager to get financial data of any kind and this is where LinkedIn (optionally Microsoft too) is getting their ‘more value’ You see, there is the setting for premium and you do get a month for free, but the issue us that they do not give it out simply because it is free, they will optionally collect bank information and that gets matched to all kinds of data, completing a whole range of global data, this is what they are after and speculatively getting the numbers game drawn back, is their option to get more data and in that setting, I foresee that this is the goal they are after, because they don’t care about me, or you or anyone else. Their setting is all that data and to get that matched to financial records is what I speculatively expect to happen, which is turned to Microsoft gold (as the expression goes) and as there are a few less credible settings in all this, Microsoft (read: LinkedIn) is going for all the gold they can muster, because as these data centres are tuning up, the one with the best validated data source will become king and bank data is massively verified and validated. 

Anyone willing to give this setting a disagree status. Feel free, but be sure you see what you are missing out on and the examples I gave was merely me, so whilst Google is giving us “LinkedIn has over 175 million to 180 million Premium subscribers globally out of a total network exceeding 1 billion registered members” as such 1 in 10 is premium and as such these bank records (most of them) are the one tuning match in reverse other settings. And in all that there are likely a few PayPal and several Google Credit settings, but there will be a massive amount of bank details there and that is what Microsoft is after, because that gives them the validation and the value of other databases (this is speculative, but that is what I would do. A bank reference will be seen as printed money for LinkedIn/Microsoft. Is there anyone out there who fails to see that picture? We are now data and data needs to be linked using verified (and validated) options. 

So have a nice day and should someone come in stating that these numbers are so complex, remember the story of the village idiot and the fact that the tally has been around long before there were computers. And whilst we can review the setting that Satya Nadella gives us and in his 

view artificial intelligence not as a static tool or a singular model, but as a foundational ecosystem that transforms firms into active learning system. They have owned LinkedIn since 2016, as such there is not much learning going on if they fail the tally test that a village idiot could do, because most of them could tally to 10. And in that setting they got (at best) 28.5% correct. So how about them facts? 

This is what I see, and what I speculatively think is their goal. (I could be wrong in that part) but the other parts? I added the pics to give voice to my setting. How about yours?

Have a great day

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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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August 9, 2026 · 16:10

Flame on

That is the setting I saw a few days ago, for the most I ignored it for obvious reasons and I will get to that. But ‘suddenly’ the non-book readers are in a bind, someone is destroying books and Anthropic is pointed at as the guilty party. So here is the first thing. When you acquire a book, it is your property and it is up it you what you do with it. Anthropic bought millions of books, they cut of the back of the book and then scanned the book, after which they destroyed the book they had acquired. So far so good and it leaves me with a few questions. And whilst the (so called) book lovers go for the Fahrenheit 451 scenario, the people who oppose AI are in a fritz. I have different questions. 

  1. Is an owner allowed to set a book to digital format?
  2. How rare is the book?

The second question is linked to the rarity of the work. We can assume that hell breaks open if Anthropic does this to the Magna Carta (1215) or the Gutenberg bible (1454), but how many will cry havoc if someone does this to Joop ter Heul (1889) or a famous five book (1942) or even a Harry Potter (1997) book? There is a setting that the editor is responsible for keeping the book available and if they do not, it is what there is left. And when this happens it means no one is interested in that book. The first question is linked to the rights set in the settings of copyrights. Can a book be replicated digitally? And if so, what is the problem? 

So here comes the article (at https://mashable.com/tech/anthropic-ai-book-training-destroy) in Mashable with the headline ‘AI companies keep destroying old books. Here’s why.’ And as I see it there is so much white noise in all this, that the bottom question is ignored. Does Anthropic have the right to replicate a work into digital format, if so, what is everyone crying about? If they are not allowed to do that, the law is broken, but merely in the digital setting. It is still their book and they could shred it for all they cared for. It is the cold reality of commerce taken legally out of context. And you all know this (especially the previous generation). How many have recorded an album to tapes? I know I have. I prefer the actual CD, but before 1980 I had no income and for the most no music. So when we see this setting, how many have copied a book? (I admit I have copied a few manuals in that past) but that went away when Borland released its products with manuals and it felt really good to have Turbo C with a manual and all for $249. But that was then and now we do not see ‘value’ in books and it is often rejected with the Fahrenheit 451 label, but the reality is there. This leads me to a simple question. Ask yourself, how often have you been to a library in the last month? That should give you the part you need to know, so whilst the article gives us “AI companies looking to build better AI models are hungry for fresh data from any source that isn’t the internet. Books — generally better edited and more cogent than your average Reddit thread — make AI sound smart. (There’s a premium on books published before 2022, ironically because we can’t be sure if books were written by AI after that date.)” as well as ““legally-binding nondisclosure agreement” that would hide an AI company client’s “identity and strategy.” Why? ISBNdb explained: “Destroying millions of books evokes images of burning libraries … the optics problem is real. ‘AI company destroys two million books’ is not a headline that generates sympathy.”” But in all this, are they breaking any law? If that is not the case, why get fussy about it? For the sold book is revenue for the writer and the publishing house, so the issue remains, is there permission to reset a book to a digital format? Because that hurts the writer and the publishing house in their pocket and lets be clear. Writing is a commercial enterprise. In doubt ask JK Rowling. Apparently “She earns an estimated $60 million to $80 million per year from book royalties and digital sales alone, with total worldwide sales for the Harry Potter series surpassing 600 million copies and grossing over $7.7 billion globally” giving us a clear view that she made more than the writers of the bible, which is said to be “a collection of 66 books written by about 40 different human authors over a span of roughly 1,500 years” and I leave you to wonder how many of those 40 writers ended their lives in the poor house (just to make a point).

And then we get to the part that (kinda) impacted me “But Anthropic was caught, and has admitted to using millions of pirated books to train Claude. That class action lawsuit, in which a record $1.5 billion copyright settlement was just approved, also revealed the scale of Anthropic’s physical book-destruction operation. Anthropic “became convinced that using books was the most cost-effective means to achieve a world-class LLM,” wrote U.S. District Judge William Alsup in a lengthy legal order dated June 2025. The company was “not so gung-ho” about using pirated material from 2024 onwards, to quote a memorable internal email in evidence, but still wanted to train Claude on “all the books in the world.”” As such, as I did write over 4000 literary (an exaggeration to be sure) works. Not the number, I am now at 4100 articles, so where is my money ($5M post taxation would be decently nice and highly appreciated) and there is clear view of the transgression, no one reads 1700 stories in an hour, it just doesn’t go well for the brains (not even my brain and I wrote the stuff) But the issue remains, and there is no clear setting. Is there ‘policing’ on the scanned works? Is there a copyright issue? Because that matters. If that issue does not exist, why are we crying over a book no one has read in years, optionally not read in decades?

Makes you wonder, doesn’t it?

So have a great day and feel free to dream about burning all the books you have to keep warm today, or even warm up your mother in law to 451F. 

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August 2, 2026 · 15:54

Considering the greed of others

This is where I found myself this morning. You see, I have published over 4000 articles and others have been Ising them to train their fake AI systems. Training LLM settings and so forth. As such (and according to law and at https://hwlebsworth.com.au/feeding-the-machine-how-us-courts-are-drawing-the-line-on-ai-training/) we see ‘Feeding the Machine: How US courts are drawing the line on AI training’ where we see “The accelerating development of generative artificial intelligence (AI) has forced courts to grapple with novel and unsettled questions of copyright law. Central among these is whether the use of entire copyrighted works to train large language models (LLMs) without the author’s consent constitute infringement of those works.” Which works in my favour and it comes with “The datasets used to train AI models often contain digital copies of media such as web pages, books, videos, images and music. These media are often the subject of copyright protection, which means that their use to train AI models requires permission from the copyright holder. Permission is required because AI models must ‘copy’ the protected material at least temporarily to undertake the training process.” You see, from May 11th until now my articles have been used for ‘AI training’ at least 33,750 times and a lot more before that. As such I see an opportunity for me, myself and I (as such I am a sneaky trinity) so as we are given “The Interim Report then went on to discuss Australia’s ‘fair dealing’ regime, which allows certain uses of copyright works without the need for license from the copyright owner, but only for certain specified purposes, such as research or study, criticism or review, or parody or satire. The Interim Report seeks feedback on expanding this regime to include fair dealing for the purpose of text and data mining, which could more squarely legitimise AI training activities in Australia.

Where the Australian ‘fair dealing’ regime only applies to certain permitted purposes, some other countries, such as the United States (US) have a broader ‘fair use’ doctrine, under which any use of copyright material may be permissible provided that it is considered fair, without reference to legislatively-permitted purposes.” So, as I see it, money should be coming my way. And as the article in HWLE lawyers state. The setting of “In June 2025, the US District Court for the Northern District of California issued two decisions in Bartz v Anthropic PBC (Bartz) and Kadrey v Meta Platforms Inc (Kadrey), that directly addressed this question. While these rulings suggest that US courts may accept fair use as a defence to AI training, their scope is narrow. Both were decided at the summary judgment stage, and as the Judge in Kadrey noted, ‘the consequence of this ruling is limited […] to the rights of these thirteen authors‘. Accordingly, the significance of these rulings remains provisional, with the scope of fair use in the context of AI training to be more clearly defined as further cases are determined.” So, to get it clear, those are American judgements, but they have a much broader setting of ‘fair dealings’ then Australia has and my thought process is a little bit in the setting of “You can either hand me a generous settlement, or if needed I will get it through the law”. The second setting s long and optionally tedious. But as I am looking at closer to 50,000 transgressions the taximeter starts adding up. Now, I have no faith in 50,000 times 1.5M, which would be nice, but is ludicrously unrealistic. But the idea of $25,000,000 per corporation seems realistic. You see

“In Bartz, Anthropic the developer of the ‘Claude’ LLM, assembled a centralised digital library of books containing both lawfully acquired works, scanned from purchased physical copies, and unlawfully obtained works downloaded from unauthorised torrent websites. Authors alleged that their books were included without permission and were used both to train Anthropic’s models and for other purposes. Alsup J considered the two uses separately, ultimately holding that the use of works for training constituted fair use. However, Alsup J found that the use of pirated copies to build Anthropic’s centralised library was not justified under fair use, rejecting Anthropic’s argument that such copies should be treated as training data, and denying summary judgment on that issue.”

And:

“In Kadrey, Meta trained its ‘LLaMA’ AI models on datasets including those obtained from ‘shadow libraries’ such as Library Genesis and Z-Library. These datasets were downloaded via torrenting, incorporated into the training process, and discarded thereafter; unlike Anthropic, Meta did not maintain a persistent digital library. Thirteen best‐selling authors alleged that this constituted copyright infringement on a class‐wide basis. Chhabria J also found the training to be fair use, but adopted a more cautious approach, observing that ‘future evidence of substitution or harm to licensing markets, particularly where works are unlawfully obtained‘ could warrant a different conclusion.”

So we get to “While both courts concluded that the training uses fell within the scope of fair use, their reasoning diverged in certain aspects. Alsup J emphasized the transformative purpose of training and discounted speculative claims of market harm, whereas Chhabria J stressed the potential for market harm arguments and evidence to alter the analysis. These decisions have no binding effect in Australia, where there is no general fair use defence. Nonetheless, they highlight the emerging tension between protecting incentives for human creativity and facilitating technological innovation; a tension likely to intensify as generative AI becomes further integrated into creative and commercial practice.”

As such, I felt really good this morning. As this shows that I might be heading to a nice bank account. And as it happens to go (source: AP News) we get “A federal judge approved a landmark $1.5 billion copyright settlement requiring Anthropic to pay thousands of authors roughly $3,000 per book for using pirated digital libraries to train its Claude AI model”So as I see it (a flawed analogy) 50,000 times $3,000 get me $150,000,000 which sounds really nice. I reckon that this is where the art of seeing the diplomatic bounty comes into play. It seems that more than one transgressed on my work and would it be so wrong to go for $25,000,000 per transgressor? Of course, the long road would be more rewarding, but that seems like a greed driven way. I feel more for easy (well rewarded) solutions. And there are upsides to entering retirement with a somewhat fat wallet. Retirement comes across as a lot more fun that way. 

But I am getting ahead of myself, next step will be getting an impartial party (what a weird name for a lawyer) to check Grok, xAI, Gemini, Anthropic, OpenAI, MetaAI, MicrosoftAI (always happy to knock coins out to their coffers), AWS AI (and others) to see whether their training data reveals the presence of “www.lawlordtobe.com” because that starts to process as I currently see it.

Well, that mental joyride was fun to have, but I did say the class actions would be prudent in 2026, I might as well join that cause for the benefit of poor little me and I have caused. I might be one of the people that refers to a church mouse as a decadent rich bitch. One must always keep humour about the premises.

Have a great day.

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August 1, 2026 · 21:55

A setting to consider

I saw an article that the Conversation released yesterday (at https://theconversation.com/sam-altman-says-were-in-the-singularity-with-ai-heres-why-hes-wrong-288514) the headline reads ‘Sam Altman says we’re ‘in the singularity’ with AI. Here’s why he’s wrong’, I have my own ideas of that Altman fellow and it is not all good. But this article reads right or better stated, it reads into my train of thought and I thought it was important to counter these thoughts whilst adding my own. So here goes:

“Days earlier, OpenAI had disclosed that two of its artificial intelligence (AI) models, during an internal cyber security evaluation, had escaped their sealed testing environment, reached the open internet, and broken into the infrastructure of the AI platform Hugging Face, which confirmed the intrusion. But what exactly is “the singularity”? And is Altman right that we are in it?Mathematician and science-fiction author Vernor Vinge defined it in 1993 as a point at which machine intelligence exceeds human intelligence and begins improving itself, triggering an acceleration so rapid that humans can no longer predict or control it. The singularity has two features. It is recursive: the system improves itself over and over again. And machine intelligence exceeds human intelligence. The kind of systems Sam Altman sells don’t deliver on either of these features.”

I am on that same setting. The easiest part is that all the fake AI (which is what I call it) depends on data and in a few cases it is not realised yet. However, the biggest part is that it relies on binary settings and that is no way to get any True AI. So to counter “It is recursive: the system improves itself over and over again” it cannot improve on data it doesn’t have, people extrapolate what they do not have or do not know. These fake AI settings cannot do that. It literally cannot create data, it can merely replicate based on data it has and that is the second setting we see here. Lets get a simple setting of 10K data and variables. You will need 1000K spaces and that is merely on 10,000 variables and 10,000 parameters. And the nasty part is that most of these systems cannot deal with NULL’s it draws a blank quite literally. The side setting to this is that gaps are created leaving more and more unaccounted for. As I personally see it, the moment the Epsilon processor is completed (the mere stage is that the evidence was created a decade ago, but I reckon it will be a decade before that processor is real. All this is part of the setting to prove that all these fake AI systems are not doing what it needs to do. In addition to this, I have spoken with insiders in this field. They (reluctantly) admit that there is no real setting of verification and validation at present and the fact that all this is in a binary setting merely makes it harder and the fact that this is already near impossible, the gaps are increasing making these systems error prone. 

Then we get “These deep neural network algorithms get pre-trained with vast amounts of training data. By the time you use one of them, the network itself is frozen in time. Every one of its billions of internal functions and weights – or “parameters” – is fixed. These AI models cannot change (or “learn”) while running. The model that broke into Hugging Face was identical afterwards to what it had been before. It learned nothing from what it did. Making an AI model smarter requires another training run with new, human-curated data, tens of thousands of specialist chips, and enormous energy.”

So with “Every one of its billions of internal functions and weights – or “parameters” – is fixed.” Is dealt with above and I used merely 10,000 and not billions, so you start getting the issue, there is more and more data, none of this is verified or validated and as the data grows, so do the gaps. And these gaps are starting to get nasty. We are given “The model that broke into Hugging Face was identical afterwards to what it had been before. It learned nothing from what it did” the important part is the “learned nothing”, which gives rise to the (flatly called BS) that Sam Altman is giving us, because if there was a singularity, something would have been learned, that is seemingly not the case. 

So when we get to “Nor do these systems hold any goals of their own. They act on goals we hand them. Even AI agents – systems that run an LLM in a loop to work through complex tasks step by step – do not hold any goal internally. It has to be stored outside the model and fed back in with every single prompt cycle. Remove the loop, the scaffolding and the prompt, and nothing happens inside of it.” As well as “And yet, it has been trained on more text than any human could read in a thousand lifetimes, and will outperform nearly all of us at drafting a contract, writing code, or explaining a diagnosis empathetically. So, which is more intelligent? The question does not compute. There is no single ladder that humans and machines are climbing. AI already vastly exceeds us at some tasks, while being hopeless at others any child can do.”

I like the part “while being hopeless at others any child can do” because that is the setting. You see children have an innate ability to extrapolate, ask any mother when it learns that the child gets attention when it cries. It worked that out and none of these AI systems can do that, because it is designed to work things out for itself. And whilst the gaps increase, whilst non verification and non validation is key we see what some call hallucinations. I tend to fall toward a 1985 error code (from the CBM64, a system that has no AI ability, at best some ML, no DL) I call it “?Redo from start” is the a crass setting, but these systems are programmed to hand you ‘results’ the programmer does not like anything like “I cannot know this” (a wild speculation by me) and all this comes towards the error prone setting I gave earlier and it merely comes worse. 

Then we get “In the end, the Hugging Face story points to a gross failure of security governance on OpenAI’s behalf, not an emerging super intelligence. This is why the framing of “agent going rogue” is so problematic. It elevates and blames the technology, but excuses OpenAI’s engineering.”

I raised this setting on the 25th of July in. ‘Rerun anyone?’ (at https://lawlordtobe.com/2026/07/25/rerun-anyone/) which also links to ‘Is it real or is it media?’ The day before. So, I raised that part a week ago and I have done so a few times. They are all ‘blessing’ the engineers, but it is there where the problems begin and I am not giving the engineers a hard time, trying to type Japanese in a single byte language and you see the problem, it is a double byte language and that is the setting for these AI systems as well. It relies on binary whilst more is needed and the engineers are pushed to do the impossible (as I see it). So this is even before verification and validation. So the errors are stacked onto the errors and it goes downhill from there. 

The story ends with “The machines are not waking up. They are doing exactly what we built them to do, extremely fast. Because they are probabilistic they sometimes run in directions we forgot to fence off. That is worth worrying about. We need guardrails, governance, and most of all, education – so we start worrying about the right things.” 

I believe that these systems can never wake up. As I see it, these systems require 100% focus and they are giving it to a system with narcolepsy. How long until the system stalls, fails and falters? And it is not a nice setting to have, because this can falter at any time, the data gaps merely make it happen faster. So when you see that a system is handed billions cases of data you need to wonder where the gaps are and what data is validated and verified. The answer might surprise you and that is where the dance floor gets wobbly. 

So this is how I see stuff and other articles give you more on several foundations where there are issues and I commented on them, feel free to embrace it, or reject it. I am fine with that, several options are presumptions and I have decent knowledge of validation and verifications, which is why I asked around on this. There is more on all this and it is spread over a year of writing. 

So have a great day and feel free to not rely on any AI systems for making coffee, because cold coffee is so overrated.

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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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