So China is really, really good at facial recognition algortihms. Like best in the world good. I wonder what they might use this for? 🤔
Maybe something like this:
Move over facial recognition, there’s a new camera-based identification technology on the scene. Welcome gait recognition. 🚶♂️
Chinese company Watrix can now identify and track people based on the way they walk. So just walk like Monty Python all the time? Nope, won’t do the trick. 🙅♂️
According to Haung Yongzhen, the CEO of Watrix: “You don’t need people’s cooperation for us to be able to recognize their identity. Gait analysis can’t be fooled by simply limping, walking with splayed feet or hunching over, because we’re analyzing all the features of an entire body.”
It appears that China is going to lead the way in all forms of tracking and recognition so it can all be bundled up in a citizen
control monitoring system. Big Brother is watching indeed. 👁️
Src: Outer Places
Ok, not really. But I can imagine that being a headline of some inflammatory “news” article. 🗞️
They’re working to remove implicit, societal gender bias from machine translations in Google Translate by changing the underlying architecture of the machine learning model they use. Basically, the model now produces a masculine and feminine version and then determines which is most likely needed. It appears that in some cases, like translating from the gender-neutral Turkish language, the system will return both versions. ✌️
This is after they announced that all gender pronouns will be removed from Gmail’s Smart Compose feature because it was showing biased tendencies with its recommendations. 📧
It’s early in the process but it appears that they are dedicated to this work and have big dreams. 🔮
This is just the first step toward addressing gender bias in machine-translation systems and reiterates Google’s commitment to fairness in machine learning. In the future, we plan to extend gender-specific translations to more languages and to address non-binary gender in translations.
Src: Google AI blog
Step 1: recreate the brain of the C. elegans worm as a neural network 🧠
Step 2: ask it to park a car 🚗
Researchers digitized the worm brain, the only fully mapped brain we have, with a 12 neuron network. The goal of this exercise was to create a neural network that humans can understand and parse since the organic version it is based on is well understood. 🗺
An interesting realization that came out of this exercise: 👇
Curiously, both the AI model and the real C. elegans neural circuit contained two neurons that seemed to be acting antagonistically, he said—when one was highly active, the other wasn’t.
I wonder when this switching neuron feature will be rolled into an AI/ML/DL architecture. 🤔
Detecting deepfakes is a problem garnering a lot of interest and effort in an ever upward-ratcheting race between the fakers and the breakers. A new approach being taken by at least two startups is to verify and record an image or video at the moment of creation to benchmark future versions against. 📸
This is probably the best method to truly thwart fakes since they can check on a price level for modifications compared to the original versus trying to spot signs of alteration in the image or video in questions. The latter method is always a footrace between the two competing interests for better methods, the former is a matter of widespread adoption. 🌎🌍🌏
Now that’s not to say that adoption is a trivial hurdle, but it’s a one-time hurdle. They key will be getting this kind of tech baked in to the devices, platforms, and apps we are already using instead of requiring people to add more to their home screens and habits. A problem and solution readily voiced by the current companies operating in this field. I’m very interested to see how this approach progresses and hope it can become the standard of our digital camera era. 🤞
Src: MIT Tech Review
Proof that the data used to train systems can impact the ethical fallout of their performance. And potentially the beginning of us getting a look under-the-hood at these still mysterious systems. I am interested to see how this approach will be applied to non-toy scenarios. 📡
Src: Fast Company
So many mixed emotions on this bit of news. Place a device in your small apartment/home and let it monitor your health via electromagnetic disturbances, even through walls. 😨
On one hand, it’s really cool to think of the positive impacts this could have. Uncovering trends, monitoring habits, divorcing the data collection from the feebleness of human memory to put a device on or charge it. And then there are the home automation aspects that it could be adapted for. The truly immersive smart home hub. 💡
On the other hand, the surveillance possibilities and sketchy corporate uses from the benign health tracking are rather terrifying. I could see China undertaking a mass rollout of devices like these to augment their camera and digital tracking network. Just as I could see insurance companies requiring the use of these devices to issue policies, and using the data to “personalize” pricing in real time, and not to the benefit of the customer. 🙀
These are exciting and terrifying times. 🔮
Src: MIT Tech Review
Essential Products is working on a phone that is largely controlled by voice commands and has an AI built in that is supposed to become a digital version of you in order to respond to messages for you. 💬
I think this sort of functionality and interaction is a big part of the future, but why a phone? 🤔
Why try to execute a paradigm shift by working in a known form factor that pits you against Apple and Android. If Amazon and Facebook both failed to launch a phone, why should an interface-altering startup succeed? Why not a watch and/or earbuds? Why not a screen less device that acts as a phone add-on to start? While I applaud the message, I question the medium. ❓
Src: The Verge
Thinking in part informed by Ben Thompson at Stratechery.
A lot of focus is placed on the US-China AI space race (guilty), but the nature of AI could make for a surprise victor. Or at least a leveling of the playing field. 🚜
There is a risk that the United States, like many leading powers in the past, could take an excessively cautious approach to the adoption of AI capabilities because it currently feels secure in its conventional military superiority.
I noticed an interesting note in the piece that arms regulations are, by and large, aren’t placed on useful defense technologies that are easily spread. Like tanks and jets (“easily spread” is relative in this case). Compared to nukes, which are heavily regulated but hard to manufacture anyway. 🏭
AI is not subject to the same manufacturing difficulties and provides far more useful. It is also difficult to draw a clear line between commercial and military uses. All of this creates a scenario that will be tough to regulate with nearly all governments incentivized to take a shot. Interesting times ahead. 🔮
Src: Foreign Policy
A while back I wrote about how I didn’t think robots would become the new consumers in capitalism. Turns out I’m not the only one. 👬
This piece scratches my economics itch in a lot of ways, but I think the heart of it is the fact that we typically believe the economy/market/capitalism operates like a rational machine and not an organism reacting to the wants and desires of a collection of irrational flesh bags. 👥
But the threat is not real for the simple reason that the efficiency of production is not the problem that economy tries to solve. The actual problem is the use of scarce means to produce want satisfaction. Both means and ends are valued subjectively. Robots do not value.
This, once again, gets to the core of my AI belief system, that we shouldn’t try to recreate human brains in silicon or assume that AGI or superintelligence will mimic humanity’s actions and desires. It just seems like egoism disguised as science. ⚗️
I want to include two quotes pertaining to value that I really liked in this piece. I think they are often forgotten or misunderstood. 💱
The natural resource it the same, but the economic resource – the value of it – was born with the inventions. Indeed, oil became useful in engines, because those engines satisfy consumers’ wants. The value in oil is not its molecular structure, but how it is being used to satisfy wants.
A good, sold in a market, is not its physical appearance, but the service it provides consumers in their attempts to satisfy wants. In other words, a good provides use value. And value is always in the eyes of the user. The value of any means derives from its contribution to a valuable economic good.
For further reading that provides another angle on why I don’t think robots and AIs will just slip into the existing capitalism and perpetuate it check out this piece by Umair Haque.
Src: Mises Institute