Machine learning – a little closer to AI?

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!!

machine learning
Reinforcement agents learning on their own

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.

Look at the dexterity of text completion. Be sure to check out my post on 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 😅


Chatbot | Are Bots without chat the future?

Computers or your phones aren’t actually all that smart, not yet. A few real world machine learning applications have become commonplace though. For instance, your photos app now recognises that you were with a dog at the park. Another example is your AI based keyboard. I vouch for SwiftKey. It uses machine learning to vastly improve auto-completion, and next word prediction. So much so, that many times it completes literally whole sentences while typing. Now, that’s pretty great and machine learning has come a long way.

So whats next? we love asking this question, and rightly so!

Different tech companies have slightly different bets to answer this question. However, there seem to be some underlying themes. For example, chatbot has begun gaining traction. Especially since Facebook launched their chatbot service.

Chatbot search trend
Notice the spike in Google Trends for Bots (in RED) in April 2016 when Facebook announced chat bots for developers

Google followed with Duo and Allo, and we know that WeChat has been doing chatbots for a while too. Conversational UI, assistant, chat based commerce and all that is apparently the “next big thing”. But is it? What does experience tell us?  well as Ben Evans nicely puts it in his blog. see original blog post here.

Is Chatbot just a bunch of “if-else-then statements”?

From my experience of using a Facebook messenger chatbot, it would appear so, it is NOT intelligent. Period. Perhaps one day, it will get there. Oh yes, and there is the Uber integration. Have you heard of a newly launched platform that does not have a sexy means to call you an Uber? Alexa, call me an Uber, Google Home Call me an Uber, Facebook bot, yada yada… Enough with Uber already. I quite like the concept of chatbot, don’t get me wrong but as Ben Evan’s blog nicely highlights, the magic dissipates as soon as the algorithm starts asking you too many questions. In the short term though, the fact that my Google photos can figure out my Christo Redeemer photos without me labelling them is definitely magic. It happens without me having to chat with anyone, or without providing any significant user input.

Christo Redeemer
Google magically finds my Christo Redeemer photos!

So, lets recap. Machine learning is great, but its not so great that it can converse with us without asking too many questions and create magic, just yet. Edit: GPT class might change this completely. See GPT2, and GPT3.

I believe the real magic is somewhere else and we should not get too distracted by the user interface such as chat. We should rather take a real world problem, let’s say “making a shopping list” and apply machine learning till the algorithm matches or surpasses human abilities at solving for the task. For instance, looking through your regular shopping lists and when you want stuff, can the algorithm automatically predict what you need every other week? That would be awesome.

Let us understand the first principle on this one.

The path of least resistance always wins. Images are better than text. Video is better than images. Automated curation of responses than asking the user to type in a full sentence. Chat requires too much user input and my bet will be on applications that make the input invisible real fast. Imagine that our machine learning shopping list app just gently notifies the user his or her auto-populated shopping list. Yes, you can then send it straight to Amazon fresh and order stuff at the push of a button. Simple, right? I know!!

Appreciate that it is a very hard problem to solve – but in my book it would definitely be magic. I am not the only one to say this, a lot of Silicon Valley pundits say that the next wave of startups would take a problem, and add AI to make things simpler. Thats what I find exciting about the future!

I am happy to be proven wrong, but hopefully we can do away with chatbots until they can truly become magical.


Ps. for any VC’s willing to fund my shopping list idea, do reach out at @abhinandanshah or the comments section 🙂

For now, bot out…