[MikeB]

https://www.worldexcellence.com/what-is-google-sparrow-alternative-chatgpt/

https://www.linkedin.com/pulse/googles-ai-sparrow-take-chatgpt-matt-

One of the key advantages of Sparrow over ChatGPT is its ability to understand the context. It uses a technique called "transformer-based pre-training" to learn the relationships between words in a sentence, which allows it to understand the meaning of a sentence even if it has never seen the specific words before. This makes Sparrow more adept at handling new data, which is a common challenge for current AI tools like ChatGPT.

Some other differences:
ChatGPT is reported as being "offline" and doesn't use reinforcement learning (you can't convince it to be racist, etc).
Sparrow is said to either be connected to the web (google) or have more frequent updates, and use reinforcement learning.

Blackbox AI + reinforcement learning hasn't been a good combination in the past due to susceptibility to learning racism. So that will be interesting.

[squarebear]

Is there a way to try it out? I notice Google have a habit of announcing amazing break throughs but never let anyone actually use them.

[MikeB]

The news articles say Google is testing it internally through 2023, so that's all I know...

[squarebear]

Fingers crossed that this one that actuially sees the light of day. I somehow doubt it though. I hope to be proved wrong. 

[MikeB]

Sundar Pichai just posted an update introducing Google Bard. May be sharing it with the public in the next few weeks ?

I think it's more of a "look up" / directory search bot than a chatbot though. More so than ChatGPT.

https://blog.google/technology/ai/bard-google-ai-search-updates/

We’ve been working on an experimental conversational AI service, powered by LaMDA, that we’re calling Bard. And today, we’re taking another step forward by opening it up to trusted testers ahead of making it more widely available to the public in the coming weeks.

We’re releasing it initially with our lightweight model version of LaMDA. This much smaller model requires significantly less computing power, enabling us to scale to more users, allowing for more feedback. We’ll combine external feedback with our own internal testing to make sure Bard’s responses meet a high bar for quality, safety and groundedness in real-world information. We’re excited for this phase of testing to help us continue to learn and improve Bard’s quality and speed.

When people think of Google, they often think of turning to us for quick factual answers, like “how many keys does a piano have?” But increasingly, people are turning to Google for deeper insights and understanding — like, “is the piano or guitar easier to learn, and how much practice does each need?”

[...]

Soon, you’ll see AI-powered features in Search that distill complex information and multiple perspectives into easy-to-digest formats, so you can quickly understand the big picture and learn more from the web...