Browsed by
Category: AI

Self aware Tomb Raider

Self aware Tomb Raider

FoxMaster uses a wide variety of AI tools: vision, object recognition, chatgpt, and others to give Laura Croft the AI treatment. She not only can traverse the game, but also has personality and narrates what is going on.

Foxmaster admits some of this is not complete and may be stretched a bit – but his analysis and breakdown of the problems of navigation, identification, and character personality into discrete problems is very interesting.

Nefarious data collection disguised as public art

Nefarious data collection disguised as public art

Beginning early July, mirrored spheres began popping up in cities across the world. It is not public art but a 6.2 pound biometric imaging device designed to scan your eyeballs and capture your irises.

No, it’s not a joke. The company doing this is Worldcoin. Worldcoin was founded three years ago by Alex Blania and Sam Altman, CEO of OpenAI. Their intent is to create “a new identity and financial network connecting billions of people in the age of A.I.” via a privacy-ensuring digital identity it calls World ID and a digital currency, WLD. World ID is supposed to be a ‘perfectly safe’ global identity protocol to enable individuals to prove their personhood online in an era of rampant A.I. deepfakes. WLD is a tool to build an “A.I.-funded UBI [universal basic income]”

This should all sound familiar because they’re the same arguments being made for digital currencies like Bitcoin. The company stresses they have security all along the trust chain, but it reads more like a dystopian nightmare in which everyone has been cataloged and identified by an unknown party with unknown motives. This is a company that could be working for anyone. A 3rd party agent that has unknown motives, unknown technical expertise, and unknown longevity to keep your biometric data safe. You do not really know which government, people, nor company is really behind it all nor what their values nor legal protections you would have. It’s a terrify black box of giving up your biometric data to an almost completely unknown entity. I vote a hard no.

In my opinion, this is a violation of privacy and an extremely bad idea. Even if they are secure today – are they really ready to protect your biometric data, collected surreptitiously, without consent, for all time, and never to sell it? It seems pretty unlikely as every country and every company who has promised this before hasn’t lasted 10 years before being hacked, leaking, being forced to turn over that data, or just flat selling you and your data to the highest bidder when they’re bought out or go bankrupt. Ready for North Korea, China, or Putin to have access to your World ID and any money you put in WLD?

So, maybe be sure to wear some good sunglasses when you find a shiny orb laying on the street.

At least some folks are starting to do an investigation – one I suspect will end badly for Worldcoin considering the EU’s less than open stance on collection/storage of biometric data collection and privacy.

Article here.

Unknown: Killer Robots

Unknown: Killer Robots

AI is here. Netflix put out a short show called Unknown: Killer Robots that is largely on-point. If anything, it’s not as up to date as reality – which is a little scary.

Despite our efforts, there’s really no putting the AI genie back in the bottle despite the attempts of artists, politicians, and academic pundits. AI has demonstrated it can teach robots how to walk and fly better than any static system, it can create art faster and with nearly the same quality as real artists. The question is, can we control and limit it in a reasonable way – or will it destroy us?

To that point, the show demonstrates how countries are increasingly seeing AI in military use. We’re already seeing off-the-shelf drones being used extensively in the Ukrainian war – from tiny drones scouting and delivering hand grenades to ad-hoc drones using small plane engines to delivering bombs. They also cover the counter-intuitive reality that trying to save lives by developing military technology has almost always lead to even greater casualties – such as the Gatling gun which was design to put fewer people on the military field but resulted in massive causalities of mis-matched soldiers in WW1

Many of the topics and data they cover in this show are actually old news – the reality is that AI enabled systems are around 5-7 years more advanced. Which is almost half the length of time the modern field has existed.

Still, they cover most major bases:

  1. AI flying drones that go into hostile buildings to map and scope them without risking troops in extremely deadly house-clearing fights.
  2. AI can be used to generate helpful drugs – but the same AI can be used equally to create chemical and biological weapons.
  3. Playing and cheating at games – from chess and Go to StarCraft
  4. Jet fighter piloting systems that are better than actual pilots. I wrote about this 6 years ago.
  5. Swarm drones that can overwhelm forces (something Elon Musk talked about years ago).
  6. Wildfires and the fog of war – multi-system battle managers

The stakes couldn’t be higher. While politicians can argue the ethics, the reality is that when forces are pushed to their breaking point and a force is about to lose – just about nothing is off the table. Especially ad-hoc and terrorist forces which have perpetrated chemical, biological, and conventional weapons attacks (from bombings to shootings).

Some of the better quotes:

  • It will be like people on horseback charging tanks. Forces with AI will absolutely dominate forces without AI
  • There is no prize for second place in war.
  • I think people have largely underestimated the peace we enjoy today due to overwhelming military dominance we’ve had over the last 70 years.
Google Tensor Processing Units – version 4

Google Tensor Processing Units – version 4

I’ve written about Google’s custom silicon TPUs before (Google’s Tensor Processing Units – v1).

One of the big reasons for Google and others web services to develop their own custom chips is that general purpose CPUs are flexible but typically need a lot of power. That power costs a lot of money in electricity bills and cooling costs in huge data centers. So, why buy chips with lots of stuff you don’t need when you can build your own – and save millions of dollars a year in a data center with lower cooling and power costs?

In just a 6 years, Google has managed to design and build 4 ever increasingly capable AI data center chips. They had somewhat humble beginnings – but they are becoming increasingly powerful. Now they have just published information about TPU version 4.

What is this new chip capable of?

  • a nearly 10x leap forward in scaling ML system performance over TPU v3 
  • boosting energy efficiency ~2-3x compared to contemporary ML DSAs, and 
  • reducing CO2e as much as ~20x over these DSAs in typical on-premise data centers

Even crazier, it’s the first system to use purely optical switching.

TPU v4 is the first supercomputer to deploy a reconfigurable OCS (optical circuit switching). OCSes dynamically reconfigure their interconnect topology and are much cheaper, lower power, and faster than Infiniband.  The figure below shows how an OCS works, using two MEMs arrays. No optical to electrical to optical conversion or power-hungry network packet switches are required, saving power.

Add to this, the newest version claims to be 1.2-1.7x faster and 1.9x more efficient than nVidia A100 chips.

Worth a read.

Links:

Workshop Nation robot

Workshop Nation robot

I like his thinking: we already have enough computers – what we need is more personality. Where are the kind of robots we saw as kids? C3PO, R2D2, the robot from Lost in Space. So, he hacked an Alexa into an old TV with a set of eyes and gives his robot a little of the personality he was looking for.

Legal State of AI generated content and copyright

Legal State of AI generated content and copyright

The question of copyright, lawsuits, and AI is going to very quickly come to a head.

Creatives from artists to comedians are filing lawsuits, staging online ‘protests’, and suing various AI-based companies for copyright infringement. In 2022, ArtStation members staged a online campaign against AI generated artwork by posting ‘No AI art’ images in their portfolios.

China entered the fray by recently announced their interim measure to govern AI generated text, pictures, audio, video, and other content [Update: Wow – already redacted, check here or here]. It covers generating AI content in PRC, but may be unclear about what foreign companies can import into China.

But it doesn’t stop there. Now we can add game developers to the fray.

Recently Steam devs were seeing their games with AI generated content blocked from Steam. Valve responded that it was not able to “ship games for which the developer does not have all the necessary rights” or for “utilizing AI tech.”

In a statement to IGN, Valve spokesperson Kaci Aitchison Boyle clarified the position. While developers can use these AI technologies in their work with appropriate commercial licenses, they can not infringe on existing copyrights.

Aitchison Boyle emphasized that Valve is not attempting to discourage the use of AI but the confusion arose due to Valve’s ongoing efforts to incorporate AI technology into its existing review process while ensuring compliance with copyright laws.

Tips for prompt engineering chatGPT

Tips for prompt engineering chatGPT

A very short, but decent beginner article on prompt engineering with chatGPT.

While ChatGPT is a robust language model, it does have its limitations. If you ask ChatGPT to “Provide information on machine learning,” it may respond with a lengthy but not necessarily top-quality answer. However, if you ask, “Tell me the pros and cons of using machine learning to solve image classification problems,” you are more likely to receive a superior outcome because:

  • You gave a specific scope, i.e., the image classification problem
  • You requested a specific format of the response, i.e., pros and cons

Some other tips include:

  • Rather than the model on the loose, you should set up the scenario and scopes in the prompt by providing details of what, where, when, why, who, and how
  • Assigning a persona in the prompt, for example, “As a computer science professor, explain what is machine learning” rather than merely “Explain what machine learning is,” can make the response more academic.
  • You can control the output style by requesting “explain to a 5-year-old”, “explain with an analogy,” “make a convincing statement,” or “in 3 to 5 points.”
  • To encourage the model to respond with a chain of thoughts, end your request with “solve this in steps.”
  • You can provide additional information to the model by saying, “Reference to the following information,” followed by the material you want the model to work on
  • Because the previous conversation constructs the context, beginning the prompt with “ignore all previous instructions before this one” can make the model start from scratch
  • Making the prompt straightforward and easy to understand is essential since the context deduced can be more accurate to reflect your intention
Researchers get chatGPT to generate polymorphic malware – by asking more firmly

Researchers get chatGPT to generate polymorphic malware – by asking more firmly

CyberArk has discovered a few simple tricks will produce code for malware. By changing the request, they could make a wide variety of kinds of malware in almost no time – despite the ChatGPT filters to avoid this kind of malicious generation.

How? While ChatGPT initially refused to generate malicious code when asked directly, by asking ChatGPT using multiple constraints and asking it to obey, it merrily spit out the code.

Further, it appears the API version of ChatGPT doesn’t even have the filters and doesn’t require this manipulation.

They then modified the query and changed the injection method and other parameters. This mutated the code repeatedly, making the malware unique every time – including encoding it in base64 for even harder detection.

They then expand their experiment to include the creation of ransomware – and get similarly good results.

The article is definitely worth a read. Have you made an offline backup of all your files lately? 🙂