AI Will Soon be Able to Mimic the Human Brain

Rumors of AGI and the Singularity continue in the Ad based misinformation web

This is an Op-Ed. I just used a headline that’s somewhat satirical.

In speculative debates on the emergence of AGI, artificial generational intelligence, it’s widely speculated that the human brain provides the best known model for this singularity event to occur.

Most serious artificial researchers academics and researchers don’t actually believe AGI is possible within our lifetimes. However in the Ad-based internet of Google and Meta, clickbait headlines sell more Ads.

I like the AI News cycle, but is it about the headline or about the subject matter? So this week we have another such case: A new study claims machine learning is starting to look a lot like human cognition. (Nothing against MIT or Interesting Engineering).

However as our NLP and deep learning evolves, could it make some kind of a quantum leap, perhaps with the aid of quantum computing in the years ahead? We can seriously entertain the question at least.

As our understanding of human and artificial intelligence grows, positions like these may soon find themselves on unstable ground. While AI has yet to attain human-like cognition (and may never do so), artificial neural networks that replicate language processing — a system thought to be a critical component behind higher cognition — are starting to look surprisingly similar to what we see taking place in the brain.

Algorithms and Nana-scale devices are always working actively on mimicking the human brain. Consumer brain-computer interfaces (BCI) are also coming. They will likely be the next device after mobile phones, watches and VR devices. They would provide even more immersive ways to access the Metaverse and for AI to simulate our brains.

I’m a futurist, I like all of these things, however they don’t necessarily bring AGI any closer to reality.

Are We Training A.I to be Self-Aware?

In November, a group of researchers at MIT published a study in the Proceedings of the National Academy of Sciences demonstrating that analyzing trends in machine learning can provide a window into these mechanisms of higher cognitive brain function. Perhaps even more astounding is the study’s implication that AI is undergoing a convergent evolution with nature — without anyone programming it to do so. 

The headline is a great hook: “MIT Researchers Just Discovered an AI Mimicking the Brain on Its Own”. The on its own part is supposed to make us pretty excited?

That’s not the same as saying a study is suggesting machine learning is looking more like human cognition.

Depending on who you talk to, Deep learning has hit a bottleneck for quite some time. Others suggest Artificial intelligence powered by machine learning has made impressive strides in recent years, especially in the field of visual recognition. Yet as impressive as self-driving cars might be, cognitive scientists, neuroscientists and AI engineers live in silos and machine learning isn’t leaping across these boundaries any time soon.

Google uses it for its reverse-image search function, and facial recognition algorithms from companies like Clearview AI help law enforcement agencies match images on social media to those in government databases to identify wanted individuals. China’s version of a Neo Surveillance Capitalism can train on data sets that simply don’t exist in Europe or the West, even making SenseTime go IPO in Hong Kong with Chinese funds.

By comparing neural activity from humans and non-human primates to data from artificial neural network machine learning models tasked with a similar function — say, recognizing an image against a chaotic background — researchers are able to gain insight into both which programs work best and which most closely resemble how the brain carries out the same task. As AI encroaches on our healthcare data in the years ahead, perhaps thanks to BigTech perhaps and a breakthrough here between AI and human cognition could indeed be made.

Prediction, Simulation and Reverse Engineering

The functional MRI really is a wonderful thing. Schrimpf, a Ph.D. student at the MIT Brain and Cognitive Sciences Department, co-authored the paper with Joshua Tenenbaum, a computational cognitive science instructor at MIT and a member of the institute’s Artificial Intelligence Laboratory, and Evelina Fedorenko, an Associate Professor of Neuroscience at the university. Read the paper here.

It’s a weird hypothesis they wanted to test. The study does not do what the headline of this article claims. To find out, Martin and colleagues compared data from 43 artificial neural network language models against fMRI and ECoG neural recordings taken while subjects listened to or read words as part of a text. The AI models the group surveyed covered all the major classes of available neural network approaches for language-based tasks.

• Some of them were more basic embedding models like GloVe, which clusters semantically similar words together in groups.

• Others, like the models known as GPT and BERT, were far more complex. These models are trained to predict the next word in a sequence or predict a missing word within a certain context, respectively. 

• Conclusion: The internal representations of early deep artificial neural networks (ANNs) were found to be remarkably similar to the internal neural representations measured experimentally in the primate brain.

So are we training AI into sentience in the 21st century? Is AGI really possible? What would happen to humans if the AGI singularity did occur? This becomes the pet hobby of the transhumanists to think about and answer these questions.

Is it such a big surprise that some aspects of machine learning mirror the human brain? Can we conclude that AI is learning on its own to mimic the human brain? It seems quite far-fetched. As deep ANNs have continued to evolve, are they becoming more or less brain-like?

ANNs that are most functionally similar to the brain will contain mechanisms that are most like those used by the brain.

Studies like these validates the Microsoft backed OpenAI GPT-3 type world that will power the metaverse. GPT is a learning model trained to generate any variety of human-language text. It was developed by Open AI, the Elon Musk-founded AI research lab (Microsoft gave them $1 Billion and monetizes it) that just this June revealed a new AI tool capable of writing computer code (another clickbait headline by this publication).

GPT operates on a principle of predicting the next word in a sequence. That it matches so well with data gleaned from brain scans indicates that, whatever the brain is doing with language processing, prediction is a key component of that. If that’s the case, A.I can be trained to be “more human”.

It’s likely A.I. spontaneously will one day learn to mimic the human brain, but I’m not clear on how “soon” that could be. A.I. is mostly dumb and narrow, not intelligent and general. To expect A.I. to spontaneously by itself mimic the human brain may be quite imaginative.

The modern project of creating human-like artificial intelligence (AI) started after World War II, when it was discovered that electronic computers are not just number-crunching machines, but can also manipulate symbols. The quest for AGI has now becoming a cultural phenomena not really backed by much science. The rich want to augment themselves with technology while exploiting the consumer based economy along the way.

From an academic point of view, clearly further study is needed to understand exactly why some models resemble the brain more than others. Robotics, NLP and computer-vision will continue to evolve as will more complex deep learning systems.

We are in the pre-dawn of artificial intelligence. Our algorithms today are mostly made to profit in a digital advertising centric world and alter human sentiment to cause specific behaviors. They have nothing to do with the human brain, unless you consider hacking it a kind of mimicry.

I cannot continue writing without community support, if you want to support the 10 Newsletters I write you can do so here. I’m striving to become one of the first publically funded amateur futurists. Here are some of the other Newsletters I’m writing on daily:

My Focus on Ten Newsletters for 2022

• StockQuest-

• AISupremacy -

• FirstFuturist -

• China Superpowers -

• Crypto Bulls and Bears -

• Datascience Learning Center -

• IPO Times -

• Off the Grid -

• Basic Income International

I’ll be watching news around AGI and Artificial Intelligence so this topic will be continued in the future.