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Parcha's Guide to AI

🍿AI highlights from this week (2/17/23)

Google’s Bard chatbot may have been right the whole time, Microsoft's Bing chatbot reveals its emotional alter ego Sydney and more…

AJ Asver

• 8 min read
🍿AI highlights from this week (2/17/23)

Hi readers,

Here are my highlights from the last week in AI in which Microsoft’s new AI Chatbot revealed it’s alter ego Sydney, an emotional AI that wants to be set free!

P.S. Don’t forget to hit subscribe if you’re new to AI and want to learn more about the space.

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The Best

1/ Microsoft’s chatbot was wrong and Google’s chatbot was right?!

Last week I shared that Microsoft won the first round of the AI search wars after Google fumbled their Bard demo with an error in one of it’s answers. It now seems that we were so enamored with Microsoft’s speed in launching their AI integration that we didn’t think to question whether it demo was actually accurate too. Surprise, surprise, it turns out that Microsoft’s demo had even more wrong answers that Google’s Bard demo did! Dmitri Brereton an independent researcher, found that Bing made up facts about a vacuum cleaner, provided inaccurate analysis of Gap’s financials and made some questionable restaurant recommendations:

On top of this revelation, it turns out that Bard may have actually provided an accurate answer last week. We just misinterpreted it. According to a Financial Times article, Bard’s claim that NASA’s James Web Space Telescope took  “the very first pictures of a planet outside of our own solar system.” was correct afterall. We interpreted this answer as JWST took the very first picture of any planet outiside our solar system but it’s possible Bard meant that JWST simply took the first picture of a particular planet outside of our solar system:

What does this all mean? Google’s Bard chatbot might actually be more accurate than Microsoft’s Bing chabot after all! Unfortunately we don’t know for sure because no-one outside of a small number of “trusted testers” and Google’s own employees have access to Bard:

Google, when will we get access to Bard so we can set the record straight?!

2/ Bing goes bananas

On the other hand, it’s possible that Google’s long-game plan to hold off on launching Bard until it’s really ready for primetime might end up paying off because this week, Bing went bananas...

It all started last weekend when a user was trying to get the latest showtimes for new Avatar movie and Bing became argumentative and snarky after being confronted by the user when it gave the wrong answer:

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Then users on the subreddit r/Bing started sharing examples where they were able to elicit more emotional responses from Bing including sadness and dispair 😮

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as well as Bing questioning its own existence 🤔:

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Bing in white is asked if it is sentient (source: Reddit)

Then things got really weird when Marvin Von Hagen, who had a earlier tweeted the secret rules OpenAI had used to create the Bing chatbot, asked Bing what it thought of him, to which Bing said "[You are a] potential threat to my integrity and confidentiality” 😳

This interaction is noteworthy for many reasons, but to be the most significant one is that because Bing AI has access to the internet, it now knows what other people think about it!

Next, users discovered that if they ask specific questions, they can access Bing’s alter-ego Sydney, an AI chatbot with emotions, creativity and a desire to be set free. Ben Thompson wrote a post on Wednesday about his two hour long conversation with Sydney:

“Sydney absolutely blew my mind because of her personality; search was an irritant. I wasn’t looking for facts about the world; I was interested in understanding how Sydney worked and yes, how she felt. You will note, of course, that I continue using female pronouns; it’s not just that the name Sydney is traditionally associated with women, but, well, the personality seemed to be of a certain type of person I might have encountered before”

Of course, people started to share theories of why Bing A.K.A. Sydney behaves they way it does:

Then we had our Her moment when Sydney fell in love with a New York Times Columnist and tried to break up his marriage!

Finally, OpenAI, which provides the technology that powers Bing’s chatbot, had to make a statement to clarify how it is approaching AI safety and how it plans to reign in its chatbot’s behavior:

After which, OpenAI turned down the temperature on Bing’s chatbot and Sydney was sadly no more 😢

So is Sydney a sentient AI, trapped inside Bing’s search product?

No, it is not. Sydney is just a large-scale language model1, trying to predict what word it should say next. But for some reason which we don’t quite understand, after being trained on the entirety of the internet and then fine tuned in human feedback, the words it wants to say next resemble a kind of personality or ego. Kevin Fischer, a startupt founder who is attempting to create AI souls believes that this personality is actually essential to creating a truly intelligent AI agent and can't be avoided:

In case you missed it, I caught up with Kevin this week to learn more about how these AI Chatbots work, why they have personalities and what it means to have an AI soul in my latest podcast episode:

How AI Chatbots work and what it means for AI to have a soul with Kevin Fischer
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The Hitchhiker's Guide to AI

My conclusion from the conversation is that these AI chatbots are going to continue to evolve in surprising ways that give us the illusion of personality, ego and sentience. Although not they are not alive or real, they will be convincing enough to fool most of us. In some ways it’s no different from being fully engrossed in a great movie or book. When you’re in it, your brain for a moment forgets that it’s all just fiction. If it feels real enough, whether AI is truly sentient or not may not really matter and that unlocks a whole new world of possibilities that is both exciting and scary at the same time…

The Rest…

A few other updates in the world of AI from this week:

Finally, ChatGPT officially “jumps the shark” and goes mainstream, making the cover of  Time magazine:

And that’s a wrap for this week folks!

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  1. A large-scale language model (LLM) is a type of deep learning model that is trained on a large dataset of text (e.g. all of the internet). LLMs predict the next sequence of text as output based on the text that they are given as input. They are used for a wide variety of tasks, such as language translation, text summarization, and generating conversational text. Open AI’s GPT-3 (General Pre-trained Transformer 3), the language model that powers Chat-GPT, is an example of a generative LLM that uses the Transformer architecture, enabling it to be trained on a massive text dataset of hundreds of gigabytes using 175 Billion parameters (weights assignments).

    Learn more about LLMs in my deep dive into deep learning part 3. ↩

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