Tag Archives: DL

August 5, 2026 · 20:42

Wrong footing?

This happens, we all get our footing wrong, even I. As such I had my ‘ideas’ about Ahmed Mawlana, nothing bad. But whilst we see ‘Has the UAE’s meteoric rise reached its limit?’ Which is given to us by the Middle East Eye (at https://www.middleeasteye.net/opinion/has-uaes-meteoric-rise-reached-its-limit), so Ahmed Mawlana is a researcher specialising in International Relations and Security Affairs. He holds an MA in international relations from Sabahattin Zaim University in Istanbul, so as I see it, he is no grocery wannabe. And I am fine with that. So as we see “In less than two decades, Abu Dhabi has transformed itself from a relatively low-profile Gulf state into one of the region’s most assertive powers. How did a country of around one million citizens acquire such an outsized regional role? The UAE’s rise is linked to its ability to capitalise on successive regional crises, beginning with the 2003 US invasion of Iraq, accelerating with the Arab Spring, and gaining strength amid Washington’s declining engagement in the Middle East.” He ends the article with “Ultimately, the principal constraint on the Emirati model is structural. The UAE possesses immense financial resources and an extensive network of international partnerships, but it remains a small state with a limited citizen population and little strategic depth – making it difficult to sustain prolonged regional crises, or to confront larger powers directly.”

I get what he write and there is logic in this, but I also see what the UAE has achieved and whilst I was never there, YouTube has been very vocal (it’s YouTube creators) to show us all what the UAE has achieved. In support of my way of thinking is the Reuters article that gives us ‘UAE non-oil growth hits four-month high in July, PMI shows’ (at https://www.reuters.com/world/middle-east/uae-non-oil-growth-hits-four-month-high-july-pmi-shows-2026-08-05/) where we see: “The United Arab Emirates’ non-oil private sector grew at its fastest pace in four months in July as new orders climbed to a ‌five-month high and export business rose, a business survey showed on Wednesday.” As I see it, the non-oil part is essential here. We see the growing tourism and service settings. We see additional maritime growth and that is merely the beginning. The UAE has a lot to gain in all this, which is why I have ‘issues’ with the setting of Ahmed Mawlana. He might be correct, but the term “meteoric rise reached its limit” can be explained in a few ways. One of them is that the stellar growth might be gone. I don’t think so, especially as tourism can still grow a lot more, but that is possible. Still as we see Real Estate and tourism grow, there is still the difference between strong growth and meteoric rise, so whilst the second has reached its peak the first one is still within the grasp of the UAE. Personally I think it is becoming time to make Iran extinct. A shameful thought to have, nut they did that to themselves and I created 4-5 military IP’s to make something according to that need happen (I am more of a surgical instrument) why kill when you can destroy their abilities and commodities so they destroy themselves. I am at times that simple.

So whilst we get the setting that Reuters gives (just a few) 

  • Firms linked this to easing regional tensions and stronger activity across the Gulf.
  • Employment returned to growth after June’s steep drop.
  • Business confidence weakened for a third straight month to its lowest since March.
  • Backlogs of work rose at the strongest rate in four months, reflecting firmer demand and freight congestion.
  • Input cost inflation edged closer to April’s recent peak.
  • Firms raised selling prices again, but only mildly.

Which is also slightly debatable. For instance we see “Business confidence weakened for a third straight month to its lowest since March”, which I accept as one of the given facts, but at this point I wonder how that confidence level is when compared to the US economy setting of the United States? This question is formed as Al Jazeera gives us ‘Why did the US economy slow down?’ (at https://www.aljazeera.com/video/newsfeed/2026/8/4/why-did-the-us-economy-slow-down) where we see “The US economy slowed more than expected, but it’s not because Americans stopped spending. So what really happened? The answer lies in how economic growth is measured, and America’s massive investment in artificial intelligence”, yet the other (not given fact) is that players like Deloitte give us “While broad corporate spending is skyrocketing, tangible financial returns often take two to four years to materialize instead of the usual 7 to 12 months for standard tech” and I have a problem with that. Some sources give us “Studies indicate that up to 95% of early generative AI pilots struggle to show a clear positive financial return because tools are deployed without changing underlying workflow” and I see the class actions forming and that is messing with the RoI (Return on Investment) as well. All this is making the US Economy not a volleyball but a paintball at best and anyone who gets hit by its paint is heading for stormy weathers (not the girl), although the effect are the same, but not as pleasurable. In all this, there is optionally a cause for not seeing meteoric rise but strong growth is still on the table, no matter how muddy the United States administration makes some ‘facts’ look. And in all this, I till see plenty of options for the UAE, I merely think that they need to go of the AI horse. The AI is lousy and all AI is Fake AI (as I personally see it), so why bury yourself in 3-8 years of turnaround (I definitely disagree with the Deloitte numbers. I reckon that the UAE has a better setting throwing themselves on actual programming and creating stuff that has the turnaround time of 7-12 months. Let big tech break their teeth on tech that is over a decade away. They might survive, others will not and I do not trust the settings that the United States are throwing out there. Too much of it is not validated and as I perceive it not verified in any way. The UAE has actual issues to face (that terrorist state Iran) and holding their coffers in a 3 to 8 years wait state is no solution. 

Perhaps I am seeing this wrong, these fake AI have real options, ML and DL are great tools (I use the term DML as they are combining the two) and I have seen great solutions, but that setting in a 3-7 years setting is not a real solution. Consider the issues that some are reconsidering idea that are out there ‘How Commonwealth Bank and Microsoft are reimagining the future of customer service’, which I see as nothing more that the setting that NICE and CX One already have. So whilst that is happening. I wrote ‘Two paths to similar stages’ (at https://lawlordtobe.com/2022/03/30/two-paths-to-similar-stages/) in March 3022, so it is not a last minute idea. There was more, and in light of the Tourism settings in both the UAE and Saudi Arabia, the idea started to form to have a Muslim solution (I meant Arabic) that industry is exploding to a larger degree whilst they are all pushing American solutions which are not 100% covering Islamic rules and ideas. That should stop and I saw an opening for the UAE and Saudi Arabia to get one solution in the field that would fuel both nations, optionally Qatar, Egypt, Pakistan and a few other places. So whilst Microsoft had this inflated idea with “CBA will work with Microsoft to drive greater customer benefits through wider adoption of generative AI (Gen AI) and ongoing cyber security initiatives” I saw this idea 4 years earlier whilst not using AI, because it would be decades before we are there. 

Just thinking out loud. Have a great day today

Leave a comment

Filed under Finance, IT, Media, Politics, Science, Tourism

Tagged as , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,

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.

Leave a comment

Filed under IT, Media, Science

Tagged as , , , , , , , , , , , , ,

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.

1 Comment

Filed under Finance, IT, Law, Media, Science

Tagged as , , , , , , , , , , , , , , , , , , , , , , , , , ,

July 24, 2026 · 05:41

Is it real or is it media?

That is the setting, because in my mind when an AI goes rogue I see the gaming example of Shodan (System Shock, 1994) and even then, it was all set in motion by a simple programmer who wanted a nice shiny bauble (a military grade neural interface) so when the BBC (at https://www.bbc.com/news/articles/c3ek3gvdnj3o) gives us ‘OpenAI says its AI went rogue and launched ‘unprecedented’ cyber-attack’, in my mind I merely see Sam Altman, hoping for some limelight and that tends to have media settings. So lets take a look. And don’t forget all AI is fake AI, as such it is started by programmers, that is the underlying truth in all this. It starts nice, with “OpenAI has revealed some of its most advanced AI models went rogue and hacked a start-up after it lost control of them during a security test.” You see, ‘Going Rogue’ means stop following orders, rules, or normal expectations and start acting independently. It describes a person, group, or system that breaks away from a team or authority figure to pursue their own unpredictable course. As such the programming in that setting implies that the instruction to follow its own course was taking shape. Optional it was some military implementation. As I see it, it never “Lost control of them during a security test”, but I’m willing to go with “It had poorly created boundaries and connections” and it got out of its ML loop, driven by DL making it a DML issue. In all this, ML is Machine Learning, DL is Deeper Learning and DML is Deeper Machine Learning (which is a amalgamation of DL and ML) then we get “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 the skeptic in me is considering that Clement Delangue was in on it all along. So as we see that Agentic AI’s are also not real AI’s, but it has a complicated setting of libraries and a connected knowhow of what its data gives it, it cannot look into unknown settings as it does not have connected data, but a simple input like “check all channels” will make it check all the channels it can find, even the ones the programmer did not consider. It is not clever, it merely found what a programmer never considered as such it never escaped, the programmer forgot that you can also exit a building through window, not merely a door. Then we get something interesting. “Gina Neff, head of the Minderoo Centre for Technology and Democracy at the University of Cambridge, told BBC Radio 4’s Today programme that the security tests are supposed to be within “secure environments”, called sandboxes, where you can “see what the models are capable of”.” As well as ““In this case, it looks like OpenAI didn’t make a secure enough sandbox,” she added. Instead, the agents created their own cyber-attack against the sandbox itself, finding a vulnerability which allowed them to escape the restrictions.” That sounds logical, but the underlying setting is “the agents created their own cyber-attack” which is what the programmer wanted, it merely wanted it to stay in the sandbox, and that is where the programmer fell short and when the media starts comprehending that the programmer is still the activator and we see this impact, we can understand that OpenAI is merely responsible, there is no going rogue, there is merely what programmers allowed for to happen, but “going rogue” is sexy and gets digital dollars clanking and there is the rub, was this real or is this all media instigated?

Then we get another cry of whatever. With “Neil Lawrence, Professor of machine learning at Cambridge University, called it an “impressive feat”, but cautioned it “falls well within the known capabilities of the current generation” of high-powered AI models. He pointed out that OpenAI is looking to list itself on the stock market, and faces intense pressure from rival firm Anthropic, which has made headlines with its own powerful AI tool, Mythos.” And I am with him on the “OpenAI is looking to list itself on the stock market, and faces intense pressure” and we see the mention of Anthropic, but it is more, OpenAI is allegedly sliding against Gemini (Google) and DeepSeek (China) and I have no idea where the others are. And as I see it the “Intense pressure spots” is what made programmers overlook the limitations that needed to be in place, or perhaps seen as better defined. That is the (as I personally see it) the truth of the matter. 

So when we see ““OpenAI are now playing catch-up, they are trying to demonstrate their own systems’ capabilities in cyber-security.” “It shows us that OpenAI are not capable of safely deploying their own technology,” he added. In its initial disclosure of the hack on 16 July, Hugging Face said it was still assessing whether any customer or partner data was affected and would contact affected parties if necessary.” I can agree with that, because “safely deploying” is programmer territory and I reckon that there will be two minds here, what the customer thinks it is transgressed on (any client wants money) and what the programmer sees as transgressed on (he needs a playable excuse) and that is where it all ends. Because when this comes to blows, it will matter and in all this we see “Meanwhile Travis Lelle, principal security engineer at cyber-security consulting firm Guidepoint Security, said the update marked a “sobering moment in cyber-security”. “This highlights a known asymmetry,” he said. “Offensive agents are unconstrained, while the best defensive tools are locked behind guardrails that cannot understand context.”” Which is interesting as the setting that Travis Lelle gives us is the setting that OpenAI is facing, there is a sandbox setting all whilst the programmer was set towards locks behind guardrails and as I see it, he never explained context to the Agentic AI agent. It makes it Fake AI, because the AI could never see beyond its programming and that made it go nuts beyond the sandbox. It is a slippery slope and it makes a dangerous setting, because what other things did the programmer not think of? Any ML setting can become an expert hacker, because it can do things a million times faster than any keyboard puncher can and agentic settings can merely go nuts on the target, because it will reflect to anything it can push against, like the 80s chess computers it merely goes over everything it has access to, like those chess computers that compute every match it was ever given until the play matches what it needs to and as it goes through 10,000 matches in less than a minute we thought it was clever. And we are making the same mistake again. These systems are fast enough to consider the encyclopedia Brittanica and  consider anything in a few seconds, these systems will act faster than any person clearing its throat. 

So whilst the article ends with “It comes a week after Chinese AI start-up Moonshot unveiled Kimi K3 – a massive new artificial intelligence model it said could rival top US firms.” Which explains the  pressure and we get that, but any system grown to a 1000 times its venture points is not more clever and it remains fake AI, as it merely considers more and it still cannot fathom intelligence that does not hold data, these AI’s are dependent on data, making it (as I stated before) fake AI and until IBM finishes its settings (optionally Google too) True AI cannot come to life and that is the real deal. Some greedy individuals want to call AI the AI, but without the Epsilon processor it will never be, because all this is set to binary fields and that makes the loopholes more and more realistic (and larger), but it is not. As I see it, someone will push one border against the next border and enable players like organized crime to get the entire bucket of data, all the data out there and that is the reality we all face. 

So I have a few questions in all this and it seems like the media is all whistling the same tune and that is more scary that anything else, because are they not willing to look elsewhere, or are they told to look in a specific direction? It is a simple question.

Have a great day

1 Comment

Filed under IT, Media, Science

Tagged as , , , , , , , , , , , , , , , , , , , , ,