Tag Archives: LLM

May 19, 2026 · 00:08

Right out of the left field

I had a mind blast a few hours ago and I don’t know what got me to this. Well I kinda do, but I was not giving it much thought. So as I was enjoying a few moments (a moment is an hour) on YouTube, I saw a video about the Epic Universe, which until President Trump decided to go the way of the Dodo, it was my ultimate intent to spend a vacation in Epic Universe, but as things are, there is no way I am going there in the next decade (optionally the rest of my life). Now my mind is set to the theme park world of Yas Island in Abu Dhabi. So as I saw the YouTube video I suddenly had an idea. This is not something I can do, but after all the idiocy settings of HR people relying on AI settings. It struck to me that these people could use a ‘simulator’ several settings from stores to amusement parks. 

So consider that HR is set to a skill level as it tends to be, but how do you hire? What triggers are you considering? That is the stage of the simulator. You are given a pool of people and the DML/LLM of that system creates the letters, the person goes through them and selects their top 5 or top 10. Then the interview and from there you get 2-3 that go through the final round. Just like your average job setting. So, as you go through the settings of HR, the simulator gives you a rank, but more importantly it shows HR what staff needs additional training. So this would be an actual simulator to improve the HR setting of a company. 

And believe me, I have seen my shares of flaky scammers (so, not HR), HR that flatly deny you, and those who seem to believe that a new starter requires 5-10 years of expertise. There are all kinds of HR and as I see it, when the AI bubble bursts, whomever will be unable to hire the right people, will go under in that AI bubble and they will not be heard of again. The setting is that the truth of the matter is that any firm will need the right people. Who that is tends to be up to HR, but how to get them seems to be unclear. As such my mind came up with the simulator setting. Based on a pool of people with DML/LLM letters so to get a mingle of types as the simulator expands into construction, retail, consultancy we will see a while range of options and there is no immediate release. To add the styles and settings will take time, but consider that the United States has approximately 36.2 million businesses and the European Union has approximately 33.5 million active enterprises across its business economy. That is a pool of almost 70 million potential customers, the retail sector is still a lot less, but it is a start and when the simulator gets the power it needs to get, the simulator gets the finance and attention to grow into something serious. So, it was just an idea and if a dedicated IT HR programmer is out there, this idea is for you. I am not getting involved in a work I have seemingly no clue about.

Anyway, that was the idea I had today, I reckon that it could use the setting of localization down the road, especially with over a billion people in India, but as I see it, the USA and EU are a decent first bet. Have a great day.

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May 9, 2026 · 10:06

Label negativity

That is the setting and I almost fell into this. I have lived by the fact that all AI is fake AI and I still believe this, just like some believe that Donald Trump cannot say an intelligent word ever, that is just the beginning, but it is all about me now. I do believe that all AI is fake AI and as such, I almost ignored news from IBM given to us on May 5th. The article ‘IBM and Aramco Explore Collaboration to Accelerate AI and Innovation Across Saudi Arabia’ (at https://newsroom.ibm.com/2026-05-05-ibm-and-aramco-explore-collaboration-to-accelerate-ai-and-innovation-across-saudi-arabia) sounds like a joke. But when you consider that AI is DML (deeper machine learning) and LLM, some say that Machine Learning (ML) is enough, but why settle for half baked? And consider that IBM has been working with Aramco since 1947 as such they have data, decades of data, as such we might frown at the words by Sami Al Ajmi, Senior Vice President at Aramco “Technology and innovation are central to Aramco’s long-term strategy. This collaboration with IBM enables us to assess how industrial AI and other mutually-agreed domains can further enhance operational excellence and resilience, while reinforcing our leadership in Industrial AI—particularly in reliability, safety, and mission-critical environments.” But when you think of it, it is a NIP methodology with near 98% data efficiency and upholstery error checking and whatever you might think of NIP think, the setting with reliable data gets to be close to actual AI, because that data is likely a lot more efficient than any other company (except IBM and Oracle) might have. As such that version of NIP will accelerate a lot all over the Aramco field. It will not have data of things it never faced before, but this setting might not cover a whole area, merely spots. And don’t take my word for it. A software package made by Systat Software Inc. called Systat worked on that premise long before people started digging into ML and DML, they set that parameter and whilst it is now Grafiti LLC (after SPSS had a go at it and became IBM) it seems that this setting is a seemingly pure win for IBM. 

A setting that should also reexamine all others to consider that whilst AI is fake, the ground work that is DML/LLM is a good field to examine and whilst we might giggle at the people mentioning and holding onto AI, DML/LLM is an established behemoth of software solutions and as I see it, when a company has been involved with IBM from nearly its infancy, that data is likely almost 100% foolish user proof and has the error setting close to absolute zero. There are people who will disagree and consider that there are likely ID10T errors (a WAN/LAN expression that has grown over TCP/IP) I believe that the Aramco/IBM partnership is almost fused together and they have worked decades together towards IT infrastructure cohesion and as I see it, the government of Saudi Arabia is all about harnessing its golden goose laying black eggs is a fusion that both parties regard as essential, the KSA to protect the income of its nation and the welfare of its citizens and IBM to keep their customer happy and content. Happy is almost easy, content is not that easy and IBM managed both for decades. As such I think that this setting is one that will work and pay off. 

So whilst I see the statement: “By collaborating with Aramco, we are exploring how emerging technologies are addressing some of the world’s most complex industrial challenges, while reinforcing our shared commitment to continuous investment in innovation” as a little presentative, the truth is that they have been working together for decades and there is little doubt in my mind that whatever comes from this will get the small percentages of gain closer towards 100% and don’t mock this setting, because Aramco is likely to gain $4.1 billion for every 1% gained, as such this is about serious money. Not some kind Azure wizard you see in almost every grocery store making them a few dollars per year. How much they will gain? I have no idea, because the oil refinery is set to a lot more than one product, but in this setting a 3% clear in the beginning is to be expected and that is over $12 billion, a billion for every month. When did you ever get that much of an increase of revenue? I only know of one man who achieved that, making it a one in 8.3 billion chance (that individual is labeled Elon Musk, look him up).

So whilst some say that this is splitting the margins of profits, I say that either you put up that $230 million a week or shut up. A clear setting of simple math and IBM can do math like no one else does. Have a great day.

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May 5, 2026 · 15:16

The path we make

The path we make is often set, for one, you cannot walk the path of (fake) AI without considering the side-roads called Data Verification and Data Validation. They are intertwined. And whenever I get to Data Validation, NASA tends to be own my mind. They have been on the Data Validation path as early as the 70’s, long before whomever runs IBM/Microsoft/Google now, they were already looking at ways to support their validation tracks. So when I see the combination of NASA and DATA I tend to look up and take notice. So when we get ‘NASA POWER’s PRUVE Tool Streamlines Data Validation’ (at https://www.earthdata.nasa.gov/news/blog/nasa-powers-pruve-tool-streamlines-data-validation) where we see “NASA’s archive of Earth observation and modeling datasets has an incredibly diverse range of uses, and assessing data uncertainty is a critical step toward ensuring the data and analyses are accurate, reliable, and trustworthy. Several factors, such as instrument calibration, atmospheric corrections, and land-surface albedo, can affect the quality of satellite data. For users working with solar and meteorological datasets, quantifying uncertainty is especially critical, as these data often inform decisions and policymaking at the community level.” And this introduction leads towards the two quotes “NASA’s Prediction of Worldwide Energy Resources (POWER) project, which provides datasets from NASA in support of energy, buildings, and agroclimatology decisions, developed a tool that enables users to assess data uncertainty for selected surface variables from POWER’s data catalog with corresponding surface measurements.” And “The cloud-based tool — the PaRameter Uncertainty ViEwer (PRUVE) — makes assessing data uncertainty more straightforward for users across disciplines and skill levels. PRUVE uses surface observed site meteorological data from the National Oceanic and Atmospheric Administration (NOAA) and surface radiation data from Baseline Surface Radiation Network (BSRN) to compare against POWER-provided surface meteorological and radiation data values. This user-friendly application gives users an opportunity to quickly confirm data validation through customizable queries.”

So when we see “By creating the free, easy-to-use PRUVE tool, the POWER team instills an additional layer of trust, empowering users to tackle some of the most important long-term weather challenges facing our planet.” I feel doubt and I do know that this is in me, not because of what is promised, but consider the settings in the example we see “a student wanting to install a small wind turbine for a study project at their college. They are limited by size and cost, so they need to make sure the predictions and analyses are reliable. As part of the study, they can use wind and other historical data parameters available through POWER to forecast how much energy will be produced from the wind turbine system. The student wants to limit the level of uncertainty in their prediction calculations as much as possible.” All whilst we also see:

  • No-coding access.
  • More than 3,000 surface sites.
  • Dynamic data visualization available for each site.
  • Ability to create maps and plots and to conduct spatial analysis on the fly.
  • User-selectable point-based descriptive statistics.
  • User-selectable site-based intercomparisons.
  • Advanced custom plotting for specific uses.

So where is the doubt? You see for the most there is no doubt in the powers that ‘reside’ within NASA, but when you see these facts, why this system is not ‘coexisting’ in the Google, IBM or Microsoft clouds? This system should (read: optionally could) be adjustable to these fake AI systems to smooth over validation and reduce error in whatever data there is. And I do know that it is not that simple, but consider the settings that are lacking now, the transference of these options might also fill the coffers of NASA and there is no way they don’t need that. And as my skeptical self realizes nearly all the data systems on the planet require additional layers of trust, but that might merely be me. 

So as I see it, nearly all data systems are set towards some setting that there is some side solution towards data validity, all whilst there is a direct need to make checking the validity of data a main priority. So what happens when this solution gets additional layers of data validation, in part in statistics to see if the validation sets statistical boundaries whether the data set in some normal way, but that limits the setting is an outlier is found, so how can that be validated? Then there are multiple factors where a value should behave in certain ways, but it would not be easy. I reckon that NASA could pull it off and it would be a tool that everyone needs. I merely wonder why no-one has considered it before. Now, I do understand that it is a tall order and I might be incorrect (read: full of it) but consider how meteorological numbers are achieved, consider that there will be error, but a setting that reduces error in validation. A system that reiterates the data given and considers whether validation passes of fails. A system like that could be made, but the issue are the outliers, so what makes an outlier valid, because if one outlier is wrongfully ‘deleted’ the data set could become invalid. So is this possible? I think that only NASA with its expertise could make such a system a reality, making data validation more readily available. Because no matter what verification process follows and whilst we await the coming of real AI, validation will still be a setting that is required in whatever data system comes to the surface of true AI. And perhaps the system will become a verification setting, both are required and neither system seems to be ‘correctly’ developed at present. It is a horrible conundrum, but it requires contemplating as such a system is needed by the time Real AI comes to all our doorsteps. 

The additional issues I see is that in this case the PRUVE tool has all these connecting data segments, but what happens when it is a little more complex? We have all our minds set to ‘connected’ data, but it isn’t that simple at times. Consider the ludicrous setting of length and shoe size. Now we can understand the setting of a 4’8” person with 17” shoes (he wishes), but is it out of the realm of possibilities? There is a girl named Shae, who claims she knows one person with that description (Game of Thrones joke). So how would you be able to validate this? Perhaps other data is required to make the clear distinction valid and how could such a system make validation reliable? As I see it, the biggest problem into validating data is being able to recognise the outliers. I see the deletion of outliers as a problem, the data loses reliability and verification become next to impossible. Its like watching a dataset limited without data from the Interquartile Range (or 3-Sigma Rule) and as I see it, whatever data you remain with makes actions like fraud detection close to impossible (unless that transgressor is extraordinary stupid). You see there is the ‘old’ premise that “Outliers can bias statistical estimates, causing inaccurate results in predictive models or misrepresentations in descriptive statistics.” I am not saying it is incorrect, but the absence of outliers could make the validity of that data a lot more dubious and finding this is a real challenge, so as far as I see it, That is a job for NASA (the keyword Superman was already taken by DC comics). 

So see this as a little trip on the brainstorming front, I definitely need a hobby and I am all out of licorice.

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May 4, 2026 · 21:58

I call it fake for a reason

I was battling what to write about and there was Elon Musk giving me a perfectly good reason right of the bat. Well, it wasn’t Elon who gave me the idea, it was his product Grok. I have always said that AI is not real because of the missing parts, and it comes with a few constraints by certain (so called) captains of industry who are lacking in several ways. It is also connected to some other things I do. You see, no matter how you come, how much you innovate the idea, you will end up with a mere 0.1%-1% of the true value of the product. Todays ‘captains’ are utterly set into the exploitation of everything they see. As such I put it on my blog. When my stuff is in the open they cannot really claim any innovation. You see the IP is no longer protected by intellectual property laws, and the public is free to use, share, and build upon these works without seeking permission from the original creator. I might get something out of it but for the most I get the satisfaction that these ‘captains’ see the loss of an idea towards everyone. If I am unable to get something out of it, it will become Public Domain and perhaps it will spread my fame in that way. Some will smile at this and call me stupid (or a fool) but I am out of their reach for exploitation. As I see it, I gave the world over a dozen options for enrichment and in this way the Indie developers get a leg up without fear that a larger player will cut them out. Small comfort. But that is what is.

So, whilst I diverted, it was for a reason. You see the AI of now is fake AI (at best), all of them are because the two elements missing are evolved versions of Shallow circuits, as stated (for as far as I know) IBM has the strongest version of this, but still another system is required, a trinary operating system. Binary will not do for AI, the setting of Null, False, True and both is required for a true AI to come and no-one has that yet. A dutch physician got the Epsilon particle made (or found), this was going to be instrumental and to evolve this in an IT setting (most likely through yet undetermined means), but I digress, what I believe to be a weakness, doesn’t make it true. Alternative evidence is needed and I found it a few times over, but in this case I will revert to my last story ‘As oil burns’ which I published on May 4th, 2026 at 12:33. About an hour later I used Grok to look at my story. The first view after an hour was:

Lawrence van Rijn’s post links to his new blog article “As Oil Burns” on lawlordtobe.com, discussing surging oil prices triggered by Iran’s closure of the Strait of Hormuz amid escalating US-Iran and regional tensions. The author, a postgraduate IT student and Master of IP Law candidate at UTS, regularly analyzes geopolitical issues like oil production shifts, UAE’s OPEC exit, Iranian attacks, and US military deployments in his personal blog. As of May 4, 2026, the X post shows very low visibility with only 4 views and zero interactions, typical of his niche personal commentary on current events.

This is what AI does? Is that really a view on what I wrote on: https://lawlordtobe.com/2026/05/04/as-oil-burns/

A story containing 986 words with more than 523 words (which is 54%) on Russia, the top line gives zero consideration on Russia, it gave me another thought, but Ill get to that later. The second view (on the same text) was after 6 hours and there we see:

Lawrence van Rijn’s X post shares a link to his own blog article titled “As oil burns,” published May 4, 2026, focusing on Ukrainian strikes against Russian oil tankers and infrastructure during the ongoing Russia-Ukraine conflict. The article cites a BBC report on Zelensky’s claims of attacks damaging three shadow fleet tankers, a warship, and a patrol boat, estimating 300,000-500,000 barrels per day reduction in Russian oil transshipments and over $7 billion in total losses from such strikes. It highlights Russia’s high military losses including over 11,900 tanks and 1.3 million soldiers, diminishing oil revenues forcing production cuts, and predicts further geopolitical isolation with limited export options remaining.

So what AI requires 6 hours to give better show of the same text? So, is my view of ‘Fake AI’ still wrong? As you can see the first part also gives no mention of the BBC and a few other parts. I got to the thought that this DML/LLM engine is allegedly used to filter out certain parts, until it can no longer hide a few things. Don’t forget whatever is done in DML/LLM is programmed by engineers, and whatever they say it is, that is what it becomes. People forget that and it is why thy fall in the AI trap, even though some clearly see that it is a fake solution. Don’t get me wrong DML and LLM are amazing inventions, but the courts will see through this and someone will blame the programmers and their bosses, this is why I saw the court cases come to blows in 2026. I particularly liked AI Misuse in Australian Courts (2026) where we see “over 73 cases identified where GenAI produced false citations.” So what AI does produce false citations? That requires a programmer. In addition, related to that is Warner v. Gilbarco, Inc. (February 2026) where we see the quote “AI to assist in case preparation does not automatically waive attorney-client privilege, characterizing broad requests for AI-generated documentation as a “fishing expedition”” Does this imply the AI uses deception to give us a “fishing expedition” or did (a massive perhaps) a programmer set this situation? As the evidence is added up, we get to see a different setting, a setting that gives notice that we should aim our attention to the programmers and their bosses. So at some point the influencers will be called into court and it is already happening “legal battles surrounding AI influencers, digital replicas, and content generation have shifted toward establishing liability for harmful outputs and defining the limits of AI-generated content protection. Key developments in early 2026 include lawsuits over AI-generated sexual content and major court decisions regarding copyright of AI-driven work.” Where we see (at present):

  • Ashley St. Clair v. xAI (Deepfakes and Platform Liability)
  • Tennessee Teens v. xAI (Child Safety)
  • Thaler v. Perlmutter (Copyright of AI Art)

And as these cases are resolved, the influencer drive of AI will dissipate and we get these bosses to ‘present’ their view, but they will be careful as they are decently unwilling (as I see it) to become liable. So whilst I will look to find a party to allocate $5M (post taxation) to my coffers, I will try to remain vigilant and see what other things some of these ‘Captains of industry’ have been overlooking. Apparently some say I need a hobby, time will tell. Have a great day.

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April 28, 2026 · 19:53

Battle lines

As per yesterday several things occupy my brain, even a new technology (which I will discuss at a later stage) today is about OpenAI and Microsoft. I was ‘alerted’ to this yesterday through through Seeking alpha. I think I heard it before that, but I ignored it. Seeking Alpha (at https://seekingalpha.com/news/4579947-microsoft-falls-as-openai-partnership-evolves-says-it-will-no-longer-pay-revenue-share) gives us ‘Microsoft in focus as OpenAI partnership evolves, says it will no longer pay revenue share’ and we are given “Microsoft (MSFT) shares rose fractionally on Monday as the tech giant and OpenAI (OPENAI) said their partnership has continued to evolve, and OpenAI’s license will become non-exclusive. “Today, we are announcing an amended agreement to simplify our partnership and the way we work together, grounded in flexibility, certainty and a focus on delivering the benefits of AI broadly,” Microsoft wrote in a statement on its website. “The greater predictability in the amended agreement strengthens our joint ability to build and operate AI platforms at scale while providing both companies the flexibility to pursue new opportunities.”” In my mind I hear “Someone has figured out that this setting is based on shallow settings, the reality is dawning on them”, so whilst we are given “As part of the altered agreement, Microsoft will remain OpenAI’s primary cloud partner, and OpenAI products will ship on Azure first. However, there is now a tweak that says if Microsoft “cannot and chooses not to support the necessary capabilities,” OpenAI can go elsewhere. Julian Lin, Investing Group Leader for Best Of Breed Growth Stocks, said the deal is actually a “net positive” for Microsoft, despite the share price reaction.” I personally believe that OpenAI might present a hardcore liability for Microsoft and they are seeking to insulate from that fallout. And it might be merely my feelings in this and that is fine, but when you see the Anthropic setting, the DeepSeek setting there are several other elements that are roaring is near ugly heard and that has to go somewhere, something has got to break and it seems the ‘staged’ setting of evolutionary contract agree ments, might be part of all that. In retrospect I have no idea how OpenAI and Musk will battle their settings (and I partially do not care either). But the elements are there and whilst we are all about OpenAI, this concept selling setting rubs me the wrong way. So whilst we ‘might’ see ‘OpenAI Misses Key Revenue, User Targets in High-Stakes Sprint Toward IPO’, all whilst some say “do you guys even use ChatGPT/OpenAI anymore? I find myself preferring Claude/Gemini to be honest”, I take a different turn, I don’t use any of them. Basically because they are all fake AI. Real AI is about a decade away, if not 2 decades. I might die before real AI is released, so I kinda do not care.

ComputerWorld, only today (a mere few hours ago) gave us (at https://www.computerworld.com/article/4163971/microsoft-openai-change-contract-terms-again.html) ‘Microsoft, OpenAI change contract terms–again’ starts with “When the two firms announced a revised agreement on Monday, it reinforced the need for enterprise IT executives to work with as many major AI players as possible, given the constantly changing landscape.” I do not disagree, but remember that Microsoft went all out about 5 years ago and whilst we saw all kinds of ‘total wreck approaches’ the ‘partnership’ went on and now that we see “the need for enterprise IT executives to work with as many major AI players as possible”, we might accept that, but we see no DeepSeek, do we? So whilst we see that Microsoft increased its stake and solidified its position as a major investor less than 6 months ago, these plans are now changing. So does Microsoft see something, or do they fear something? And then ComputerWorld gives us “One key component within earlier versions of the Microsoft-OpenAI deal was the change in the relationship if OpenAI ever achieved artificial general intelligence (AGI), a term that eludes a concrete definition but generally refers to AI that equals or exceeds human capabilities.” I find it funny because of all these definitions across the fake AI field. Do they really not see that it is about to fall apart? (Story to follow likely tomorrow). And when this war of the fakers is seen (OpenAI, Google, Anthropic) there is every chance that OpenAI ends up in last position (see another ‘winner’ chosen by Microsoft), but this war setting is almost real, but until there is a real revenue stream coming in, there is unlikely to be a real winner. So whilst ComputerWorld focusses on the market changes with “Analysts and consultants generally agreed that this altered agreement will reinforce, and should extend, the current enterprise IT trend of hedging bets by striking arrangements with a variety of AI providers, including the major hyperscalers. Beyond future-proofing enterprises’ AI efforts, some of those agreements are for practical issues, such as the need to work with global AI firms specializing in different languages that the enterprise needs.” And you already know where this goes next. So, when was the last time you saw this kinda bla bla settings in the last 45 years? I tend to go back to the early 90’s where they all tried to sign businesses up to concept selling, all whilst there was no revenue stream detectable. We see it now here. I get that analysts are not the most revenue sturdy people, but consultants need their revenue streams. It is their bread and butter. And what was that “for practical issues” about? You see ComputerWorld writes a good story and revenue is mentioned four times, three is shown next “In addition, the company’s role as a major investor in OpenAI is driving a different revenue relationship, it said: “Microsoft will no longer pay a revenue share to OpenAI. Revenue share payments from OpenAI to Microsoft continue through 2030, independent of OpenAI’s technology progress, at the same percentage but subject to a total cap. ”” interesting how salespeople are not that fuzzed about revenue. It is their income and bonus setting. So what was this really about?

Wouldn’t we like to know this? Just a few settings for todays stride in the coming week. And now I need to contemplate what I next write about the bad news, or the new technology. My conundrum  for the last 4 hours of the day.

Have a great one today.

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April 25, 2026 · 23:45

Accusation without evidence

That is the path I saw today on the BBC (at https://www.bbc.com/news/articles/cpqxgxx9nrqo), now hear me out. Even as we are being told ‘White House memo claims mass AI theft by Chinese firms’ we have to acknowledge that it comes from that same place that gave us that “‘someone’ claimed “$18 trillion” in new investments”, “prices are down” and “Ukraine for starting the war with Russia, suggesting they should have surrendered territory to avoid it” as such I am willing to disbelief this. Also China has DeepSeek and it does so (it’s speculations) at a fraction of the cost.

And whilst we are getting “The White House has said it will work more closely with US artificial intelligence (AI) firms to combat “industrial-scale campaigns” by foreign actors to steal advances in the technology. Michael Kratsios, Director of Science and Technology Policy, wrote in an internal memo that the administration had new information indicating “foreign entities, principally based in China” were exploiting American firms.” My mind goes not different directions. The first being:

If you have shattering IP valued at billions of dollars you have proper cyber security installed. That is merely my thought, others might have another opinion. 

My mind is racing towards a different setting. You see, OpenAI and its ‘co-conspirators’ are not delivering on the premise that gave too many people well over half a trillion dollars want to see return on investment and none is coming and now (not unlike the concept sellers in the 90’s) they need a blamable party. So what is easier than to blame China? Now, I am not saying that China is innocent, but in all this one might need evidence to make a case and none of it seems to be coming. As such we are given ““foreign entities, principally based in China” were exploiting American firms. Through a process called “distilling”, such firms are essentially copying AI technology developed by US companies, he said.” OK, I’ll bite, so where is the evidence? Why, if this distilling is a problem are these outputs not better protected, so there is no ‘distilling’? Simple question, perhaps when Oracle was needed, the cheapskates decided to rely on Azure? I have no idea, I am merely offering options as the evidence is clearly lacking. 

So whilst the article ens with “While Kratsios did not name any foreign entities, leading AI companies like OpenAI and Anthropic have said they are dealing with such distillation activity.” I reckon that the distillation culprits like House Spirits Distillery and Angostura Distillery were made exempt? 

You think that I am making a funny and I was, but this has been going on for months and these so called high priced (fake) AI corporations have been absent in their cyber security? How does this distilling happen? All things missing from the BBC article and are unlikely on the mind of the White House as the article seems to imply it comes from the very beginning where we saw “it will work more closely with US artificial intelligence (AI) firms to combat “industrial-scale campaigns” by foreign actors to steal advances in the technology” you see, the first part would be ‘How did they achieve this?’ Which we do not see and the state of cyber security we don’t see either, both seem rather obvious in that setting. 

So as I said China might not be innocent, but in that same setting we see that the United States and their (fake) AI firms are apparently clueless. Don’t take my word for it, just look at the scraps on this table and see where the crumbs aren’t dealt with and I see no part in all this that shouts ‘China is guilty’ that would require actual evidence. So if that is seemingly is not required counter the idea of this AI scheme to be the part of a scam to wipe out trillions on the exchange, which might be the case, but the setting of ‘no evidence’ is apparently in effect and that goes both ways. As I see it, someone wants to see evidence of AI and whilst they invested billions, there is a greed driven setting that the profits all go to China as they stole the plans, but is that really so? Even distilled plans need refinement and the source data is missing. So, how would they proceed? The setting does not make complete sense to me. Any innovation requires a foundation, even DeepSeek would like to have one, or it is simply a sifting solution and the power remains with these innovative wannabe’s (sorry, a paraphrased term).

So have a great day and wonder why the accusation was made, because that setting is likely to be in dollar numbers and where is that money now? Have a great day.

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March 22, 2026 · 01:28

I am not economical savvy

That is the setting and we can conclude that I am intelligent, but not that economical savvy. I have known for the length of my years that if you spend less then you get, you might get rich at some point. I know it is a little simplistic, but I am not an economist. I know data, I can read, write and comprehend data, almost any data. So when I saw something almost a week ago, I wrote ‘Is it insight or data?’ On March 16th (at https://lawlordtobe.com/2026/03/16/is-it-insight-or-data/) and I stood behind Oracle, not because I am so economical, but because I know technology and Oracle is an essential technology. In some ways it is now chased by Snowflake, but that is the nature of the beast. Oracle might be at the top, but it is forever being chased by whomever wants to get into number one. Snowflake is speeding past all the others, but it will not (for some time) go past Oracle. So when I saw that Oracle had half a trillion in their pipeline, the other news made little sense and I wrote about that and 4 days later (the day before yesterday) we get a fool, a Motley fool no less (at https://www.fool.com/investing/2026/03/20/news-oracle-billion-backlog-ai-stock-buy/) give us ‘Oracle’s $553 Billion Backlog Could Make It the Most Important AI Stock of 2026, But Is It Too Late to Buy?’ Pretty much exactly as I said it was. But they give us more. We also see “It’s worth noting that Oracle stock has lost 49% of its value in the past six months, owing to multiple concerns, including a reliance on OpenAI for a significant share of its contractual backlog and taking on sizable debt to build artificial intelligence (AI) data centers. However, those concerns took a backseat after Oracle’s beat-and-raise quarterly report. Let’s see what worked for Oracle last quarter. Then, let’s take a closer look at its valuation to find out if it’s too late to invest in this AI stock that has the potential to soar impressively for the rest of the year”, with an additional “Oracle’s quarterly revenue jumped 22% year over year to $17.2 billion, exceeding the $16.9 billion Wall Street estimate. The company’s non-GAAP earnings growth of 21% to $1.79 was a bigger surprise, as analysts would have settled for $1.70 per share. The company’s cloud infrastructure business also outperformed expectations, with revenue increasing by 84% year over year to $4.9 billion. That was higher than the $4.74 billion consensus expectation. Even better, Oracle’s cloud infrastructure business is likely to continue growing at a terrific pace in the future. Its remaining performance obligations (RPO) jumped a whopping 325% year over year in the quarter to $553 billion.” Now lets be clear, I get most of that data, but unlike that fool Motley there is a lot I do not see, mainly because I am not an economist. 

And here you might think that there is confusion, because I have (and still) say that AI does not yet exist. But data does exist and when it comes to data Oracle is the Rolls Royce of data systems. So, whatever these people want to make you believe, they can do it better with a good data solution. And all DML (Deeper Machine Language) as well as interactions with LLM (Large Language Models) require the best solution (which gets you to Oracle with optional Snowflake) so whatever data solution these people select, they need to rely on their data ventures and that puts Oracle in the picture and when you comprehend that, the half a trillion dollar pipeline starts making sense. 

What astounds me is that some people like to make some kind of consideration and as I see it, Oracle is a long term investment. You might think it is about the wealth of Larry Ellison and you would be partially right there, he brought Oracle to life (as the saying goes) and whilst some people are in it to play the markets, Oracle is above that. It is the safe place to put your dineros (as the expression goes). 

So why Oracle? As I see it, for over 30 years the people who wanted to get into data emulated and copied what Oracle did and called it innovation, but there is only one Oracle, the rest is almost a joke (OK, Snowflake might be the exception, but it is not as great as Oracle). Some tech firm bought Sybase and flogged it off as THEIR baby and they did well, but it is not the same a being the actual innovator. So as some call it, some stock is up to scrap and as I see it, it would be Oracle. 

Whilst I am writing this something occurred to me and this falls on the mattress of Google. We are given “Oracle (ORCL) is widely considered a strong buy by analysts following robust Q3 2026 earnings, surging cloud demand, and a massive $553 billion backlog. With a 4-star rating from Morningstar, the stock is viewed as moderately undervalued with significant growth potential, although some analysts caution about high capital expenditures and heavy reliance on AI partner OpenAI.” And the two points are in the first “following robust Q3 2026 earnings”, so they decided on earning that will not be completed for another 6 months? Explain that to me, because as far as I know time travel is not a valid method of predicting earnings. Then we get “heavy reliance on AI partner OpenAI.” Why reliance? So, who calls the shots there? Is there a given that OpenAI demands Oracle? I get that people who are in the ‘spell’ of AI require Oracle, that makes sense. But think of that for a moment. There are numerous data vendors. Do you think they all select Oracle because Microsoft/AWS/Google/IBM are all Dodo’s? It is all dependent on what solutions these customers have now and that might set the bar for what data is selected, don’t get me wrong. Oracle is the best as such I applaud their actions. But I have seen my share of boardroom meetings where someone was in favour of whatever they had, as such I have an issue on the use of ‘reliance’ as in ‘heavy reliance’, but that might just be me.

In the end, we all take what we can get and data people select Oracle for the simple setting that it is the best. So select what you think is best for you and consider that Oracle will continue no matter what, because there can only be one number one. 

Have a great day, It is not Sunday here. Time to imitate a sawmill as It is massively past midnight.

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February 27, 2026 · 11:06

The fear behind us

There is a setting, one that requires scrutiny and one that demands closer looks. You see, I do not completely agree with the setting that The Guardian gives us (at https://www.theguardian.com/technology/2026/feb/26/how-to-replace-amazon-google-x-meta-apple-alternatives) with the illustrious title ‘Leave big tech behind! How to replace Amazon, Google, X, Meta, Apple – and more’ the first big thing is that there is no mention of Microsoft in that title. So that is the very first thing that comes to mind. Especially as CoPilot was mentioned earlier this week of sifting through our confidential emails. I can drop the ‘alleged’ as Microsoft admitted to this and basically said ‘Oops’ as an implied reason. So what gives?

It starts with “So many ills can be laid at its door: social media harms, misinformation, polarisation, mining and misuse of personal data, environmental negligence, tax avoidance, the list goes on. Added to which, Silicon Valley’s leaders seem all too keen to cosy up to the Trump administration, to shower the president with bribes – sorry, gifts – and remain silent about his worsening political overreach. And that’s before we get to the rampant “enshittification”, as the tech writer Cory Doctorow describes it, which means that by design many big tech products have become less useful and more extractive than they were when we originally signed up to them.” OK, I can go along with this. And the sentence “many big tech products have become less useful and more extractive than they were when we originally signed up to them” gets a mention from me because some of these ‘culprits’ seemingly have no idea what innovation is, for the you have to look towards China, specifically Huawei and Tencent. So we get to the first hurdle. 

“Google has cornered 90% of the search market for the past decade, but it is often no better, and sometimes demonstrably worse than its rivals, perhaps on purpose – Doctorow has called Google: “the poster-child for enshittification” citing its alleged strategy of worsening search quality so that users spend more time on the site. But changing the default search engine on any device is extremely easy. I’ve been using Ecosia for years. Instead of using your searches to fill corporate coffers, it uses them to plant trees. The Berlin-based company claims to have planted nearly 250m trees since it launched in 2009 (you can even get your own personal counter to feel extra virtuous). Ecosia commits 100% of its profits to climate action (over €100m so far), produces more clean energy than it consumes via its own solar plants, and collects minimal data on its users. Ecosia’s search results are not always as thorough as Google, admittedly (in the “news” category, for example), though the toolbar does give you options to search via Google and Bing if you need to.” The issue is that Ecosia is for all intent and matters Microsoft Bing. So this is seemingly a sales talk by a journalist because there is a massive problem finding anything by Microsoft reliable. And then we get the real stuff, Microsoft knows it is in hot waters, so we are given “The French company Qwant is similarly privacy-oriented (its slogan is “The search engine that values you as a user, not as a product”) and is now mostly independent (having started out based on Bing). It is now partnering with Ecosia to build a new “European search index”.” Yes but Microsoft is American ands as such your data will be copied and frowned on, browsed through to all their hearts content. If this is wrong, Ecosia and Qwant better clearly state that they are independent of Microsoft, because it is still the issue in Europe and for what they state the their DATA is completely secure, the issue becomes where are the backups? If they are on an American cloud or server, the setting of privacy is set to 0%. 

I can agree with the Browser chapter and even as I still rely on Google (it has never failed me), I get that no everyone is in that chapter of things. I get the Office part. I myself downloaded LibreOffice (download only, no installation yet) and I will look at it at some point, the Apple apps do their work brilliantly. So we are given “Many of them, including Austria’s military and local governments in Germany and France, are switching to LibreOffice, created by the Berlin-based, nonprofit, The Document Foundation. Businesses and individuals are doing the same. Ethical Consumer has used LibreOffice for some time, says Fraser. “It’s an open-source version of Word, and all of the Office tools. It works and looks basically the same.”” I personally reckon that this is the problem Microsoft has and getting the data from Ecosia might be their last handhold to European data, this is not a given, but I expect that this is the inside not Europe to some degree. And whilst everyone is concerned with the privacy of data, I reckon that similar to the setting of 1998-2002, no one is digging and questioning the stages of backups. But that might merely be me and as I am no longer living in Europe, I casually don’t care.

Then we see the mobile settings with a shoutout to Fairphone in the Netherlands. I have nothing against Fairphone, but it always makes me wonder if Fairphone had the same idea that Tulip had in the 90’s. That doesn’t make it wrong, it is merely a Business Ploy that should be considered. I am now and always have been a Google guy. So when we see “There is a catch: most of these phones still rely on Google’s Android operating system, but any phone can be fully “de-Googled” with the /e/OS operating system (it comes as standard with Murena phones), developed by the global, mostly European, nonprofit, e Foundation.” I can think of a way where Google can set this with their Pixels. When the consumer can select Google or A Linux version that does most of the stuff, Google clearly wins in several chapters. I reckon that these flower can merely snap market share because of this, when Google leaves it to the consumers, Google wins nearly automatically. Oh and in all this there is no mention of HarmonyOS in this and I reckon that these smaller players are adjusting to HarmonyOS as we speak, or cater to, or appease that branch. Not everyone in Europe is ‘China hating’ material. And that is merely the smallest setting of these parts. I am personally not touching the shopping side. I was raised as a follower of ‘Support your local hooker’ a phrase from the late 70’s. In that age we got malls, supermarkets and such and die to that escalation loads of local stores went through a foreclosure setting. In that same way I don’t order from Amazon. I have nothing against Amazon and they closed the gap of rural places having no way to get stuff to them having plenty of stuff and over 60% or Europe and 71% of rural USA is now served. As such Amazon did them right. I just believe that I should get to the local stores to get what I need. I only had to resort to Amazon twice in the last 10 years. So I am happy. And all these Amazon haters can go sit in a corner trying to work out the function of a cheese slicer (revelation: the red corners that are diminishing have figured it out).

But my issue is that Microsoft is shown in a ‘favorable’ light, they aren’t and they aren’t due that setting as I personally see it. The fear behind this is not the Big-tech, it is the policy that comes through the CLOUD Act (2018), it gives America too much ability to get to out data and in several cases non-American IP, which is even more frightfully. these hundreds of data centers have no reason to exist if the CLOUD Act (2018) what made illegal, that is how I see it and there is no saving Microsoft, because we get ‘blunder’ after ‘blunder’ and how long until we get another ‘Oops’ setting but now corporate IP was set in some AI hole? That is the larger fear that I see and there is no stopping it, whilst corporations are breathing the AI cloud through wannabe’s who want to move up in the world, that data is most likely to get compromised and as corporations are not setting the HR and data loops to any scrutiny, this is likely already happening and will continue to happen until the then valueless corporations see that they had to act a lot sooner than the day before all their data is in other hands. We already have Thomson Reuters v. ROSS Intelligence (2025), Bartz v. Anthropic (2025/2026), Disney & NBCUniversal v. Midjourney and the best case is United States v. Heppner (2026) where we see that documents drafted using a public, consumer-grade AI tool were not protected by attorney-client privilege or the work product doctrine. And that is the setting that people miss. Should someone at IBM use that setting this work becomes public, so consider that this is not IBM, but Microsoft using Copilot or OpenAI (ChatGPT) the work of your corporation becomes for all intent and purposes Public Domain, did you sign up for that?

There is plenty in the article that makes sense, but the ones that aren’t mentions are a larger fear creator than anything you are trying to hide from. Just an idea to consider. Have a great day this day.

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February 18, 2026 · 15:23

The deluded new congregation

That is the thought I had when I looked at ‘AI challenges the dominance of Google search’ (at https://www.bbc.com/news/articles/c1dx9qy1eeno)  where we see a picture of a pretty girl and the setting that “Like most people, when Anja-Sara Lahady used to check or research anything online, she would always turn to Google. But since the rise of AI, the lawyer and legal technology consultant says her preferences have changed – she now turns to large language models (LLMs) such as OpenAI’s ChatGPT. “For example, I’ll ask it how I should decorate my room, or what outfit I should wear,” says Ms Lahady, who lives in Montreal, Canada.” It seems like a girly girly thing to do (no judgement) but the better angels of our nature, stated by Abraham Lincoln in his 1861 inaugural address requires reliability and the fake AI out there doesn’t have it, it is trained on massively inaccurate data, some sources give us that Reddit and Wikipedia is the main source of trained data in excess of 60%, whilst it uses Google data for a mere 23.3%, as such your new data becomes a lot less accurate and when I seek information, I like my data to be as accurate as possible. And of course she adds a little byline “Ms Lahady says her usage of LLMs overtook Google Search in the past year when they became more powerful for what she needed. “I’ve always been an early adopter… and in the past year have started using ChatGPT for just about everything. It’s become a second assistant.” While she says she won’t use LLMs for legal tasks – “anything that needs legal reasoning” – she uses it in a professional capacity for any work that she describes as “low risk”, for example, drafting an email.” I would hazard the thought that she wasn’t even old enough to touch a keyboard when she ‘early adopted’ Google. We now see more and more the setting that influencers (to be) will shout the “AI vibe” but the setting is nowhere near ready and whilst we look at the place, consider that she might be doing it in French (Montreal, Canada) so where is the linguistic setting in all this BBC? So whilst we get “A growing number are heading straight for LLMs, such as ChatGPT, for recommendations and to answer everyday questions.” My thought is ‘A what cost to our private data?’ And then the BBC makes a BOOBOO. We are given “Traditional search engines like Google and Microsoft’s Bing still dominate the market for search. But LLMs are growing fast.” A booboo? Yes, a booboo. You see Microsoft Binge holds a mere 4% market share whilst Google has 90%, this story is nothing less than a fabricated setting with a few people dancing to the needs of Suzanne Bearne, the technology reporter. What? Nothing to write about?

I did very much like the statement “Professor Feng Li, associate dean for research and innovation at Bayes Business School in London, says people are using LLMs because they lower the “cognitive load” – the amount of mental effort required to process and act on information – compared to search.” I am willing to accept it as the sheepish hordes are all going towards the presented bright light of ChatGPT, but nothing more than that. I wonder when people will learn that the AI trains are not that, nothing like AI trains and for the most they seem to be the presented solutions that faster is better, but the tracks are not that reliable at present and they forget to give that view on the setting of that some laughingly call AI. And the end of this article does give an interesting ploy. It comes with:

“Nevertheless, Prof Li doesn’t believe there will be a replacement of search but a hybrid model will exist. “LLM usage is growing, but so far it remains a minority behaviour compared with traditional search. It is likely to continue to grow but stabilise somewhere, when people primarily use LLMs for some tasks and search for others such as transactions like shopping and making bookings, and verification purposes.”” That sounds about right and it comes with a dangerous hangnail. It becomes a new setting where phishers and hackers can get into the settings of YOUR data, because there is always a darker side and that side is brighter than getting Google to surrender what they have and often it is not laden with identity markers, but then I could be wrong. 

So whilst some will like the new congregation, the dangers of that new congregation is not given to you by the media, because caution does not translate to digital dollars, but flames of disruption are. Just keep that in mind.

Have a great day.

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February 16, 2026 · 21:33

Questions

That is what I was thrown, questions and quite a few. To get there I need to take you on a little journey it was around 1988 I got my fingers on some defence data (can’t tell you which one) the data shows results of some kind (I had no idea at that time what results they were) but the part that was, was the fact that they had log files and these files gave locations. It comes with the setting of log files. These files gives the hacker way too much information, what solutions are being used, what IT architecture was in play, in those days I was a simpleton. I never realised the power that this kind of information had, or as some hackers said in this setting “Copy me, I want to travel” This part matters, because around 2014 (after the traitor Manning gave the files to Wikileaks) I got my hands on some of them. The compression used was one I had never used before and it took a few days to get the program. What I saw was that log files were here too. It wasn’t that obvious, but I noticed them and these log files gave part of that current architecture to whatever hacker got (or was given) access to it. So a setting that was about 37 years old. This setting has been in place for that long a time, so as you see this, we can start with the articles, so keep what I just gave you in mind.

The article was given to us by NDTV (at https://www.ndtv.com/world-news/openai-accuses-deepseek-of-distillation-what-it-is-how-it-works-us-china-tensions-11002628) I got the news from Reuters, but they are behind a paywall, so NDTV gets the honour. We see ‘OpenAI Accuses DeepSeek Of Distillation: What It Is, How It Works’ and hit comes with “In the AI world, distillation is a common technique where a smaller or newer AI model learns by studying the responses of a larger, more advanced model” And we also see “The company told the House Select Committee on China that DeepSeek allegedly relied on a technique known as “distillation” to extract responses from advanced US AI systems and use them to train its own chatbot, R1,” according to a memo obtained by Reuters. The American AI giant stated that the Chinese firm was finding clever ways to bypass safety systems and trying to take advantage of the technology that US companies spent billions of dollars developing.” Now consider that (according to some) “OpenAI is valued at approximately $500 billion, cementing its position as the world’s most valuable venture-backed company” when you get that and when you realise that log files could be used to ‘distill’ information. Now imagine that this information could lead to corporate knowledge? So when you realise that this setting was out there for almost 40 years, do you think that more concise solutions would have been needed? So when we see that Sam Altman is prone to ‘excuses’ like the setting with Nvidia, the stage with Microsoft and now this? What is Sam Altman not telling its audience? Isn’t anyone taking that leap? So whilst I remember that at least one of the Pentagon routers still have the admin password to “Cisco123” you might consider the setting that this article (as well as the Reuters) version is a preamble to bad news and when you consider that Americans have an overactive dislike of anything Chinese (like DeepSeek)  and when we get to “In the AI world, distillation is a common technique where a smaller or newer AI model learns by studying the responses of a larger, more advanced model. Instead of training that model completely from scratch, the newer model observes and mimics the advanced model’s answers and behaviors.” The setting I gave you makes the setting of better protection even more sense. Especially as this impacts a expected $500,000,000,000 valuation. There are days that I don’t have that amount in my wallet (100% of the time) so I am left with questions. So in the first, why was there no better protection and in the second, how did DeepSeek get access to them. I would normally tend towards the inside job notion. And that setting is seen (personally and speculatively)  on a few levels and in a few ways, but happy go lucky, the media isn’t on that level yet (or ever). So does anyone else have the idea that something doesn’t seem to add up or match to the stage of a 500 billion dollar solution? Just a few questions come to mind at this point. 

Have a great day today, there about to have breakfast in Toronto and I kinda miss than frisky cold atmosphere whist drinking an elephant coffee (Jumbo cappuccino with full cream milk and three raw sugars) whilst nibbling on some sandwich (nearly anything goes there). So enjoy your day today.

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