Before we get to Machine Learning, I want to introduce you to a story my kid loves – “The Gruffalo…”. A mouse walking through a jungle meets a series of predators. He escapes each and every one of them by making up stories of a non-existent creature called a “Gruffalo” and scares them away. There is a twist though – creature is for real!! The mouse manages to pretend his way and get out of the pickle – In summary, the little brat outsmarts his own creation 😅
I wonder sometimes if Machine Learning is like a Gruffalo!
Frankly most of the hype around it seems make-belief. The biggest disservice to the field of machine learning is the word AI. It promotes hype and fear that AI will trounce humans or will one day take over the world. We at least today seem to be far from such a dystopian scenario. Almost all science community agrees that we are far away from achieving “Artificial general intelligence”.
Let us extend the Gruffalo metaphor a bit – while most agree about the wrongness of fear mongering on AI, we should be open to precaution. Perhaps the creature is not make belief after all! Very recently I have come across 3 things that have given me the creeps when it comes to what machine learning can become!!
Hide and seek intelligence!
Elon Musk’s Open AI just released a paper in which they describe a simulated training environment in which they make agents (RIL) play a game of hide and seek. The environment progressively introduces 6 strategies and counterstrategies. What they observed was incredible, they observed emergent complex tool usage. As an example, hiding agents using boxes to block doors so that they cannot be discovered by seeker agents. Seeking agents use ramps to jump over obstacles. Hiders use ramps and hide these in rooms to prevent use by seekers to jump. If this type of “completely un-programmed” behaviour is not intelligence then I don’t know what is! Please read a blog post by OpenAI here.
Google Duplex Machine Learning enable a natural sounding calling service for restaurant bookings etc was out of this world – borderline spooky as well
This is the first time synthetic speech was indistinguishable from human speech. To use it, improvise it and do it at Google scale was simply an incredible feat for speech synthesis, natural language understanding and processing and apparently a factory of human agents as well 😄 jokes aside this really gave me goose bumps. Google uses RNNs for this. See conceptual architecture and the link to original Google blog here.
Breakthrough language model GPT 2 released recently by OpenAI achieves state of the art performance on many language processing benchmarks and performs rudimentary machine translation, comprehension and summaries
I don’t think people appreciate how much of a big deal this is. Basically you feed the model some seed and it generates many many paragraphs of coherent human like text on its own, replete with stories, meaning and full sense. If you read it you will not believe that an AI wrote it. You add this and you have a frankenstein-ish monster on your hands. This can be used to generate fake news en masse. and would be hard to detect it. It can impersonate people. On a positive side it will make bots, writing assistants translation, and knowledge systems remarkably useful and human like! For an AI that is the ultimate goal. See an example below from openAI original blog post. See also a post on newer version GPT3.
While it is impossible to list down many incredible feats achieved in this path breaking tech, I wanted to cite a few examples that gave me the goose bumps. You should also check out DeepFakes and MuseNet.
I believe we are looking at building blocks of higher intelligence getting better and better, you could say we are helping machines evolve faster in their own right – but most still believe we are far away from AGI, or singularity… But are we?
Ps. This blog post was written by a human, and if you don’t believe it, ask the Gruffalo 😅