overweight and depressed. His shirt is screaming

hi! the point the video is trying to make is that both NLU and LLMs have their own pros and cons - where the real benefit presents itself is in combining the two technologies together to get bot accuracy (NLU) creativity (LLM). hope that helps!

It's the key and their moment of glory cannot be denied... inspiration to some, lesson to some...🎉

the real discussion starts at 17:30 before everything was a fluff, typical management consultant bs.

​@@techiepmtrue that

Why is that 'unfortunate' as you put it? From my perspective as an "engineer", management consultants etc are lower life forms in terms of their contribution to basically everything they contribute anything to, in that their contribution, their "value" is often just more or less that they, if they are good, are able to take ideas from the techie side of things and essentially translate them into the sort of language that the check pushers understand, ie how it will make money, in more concrete terms than the techie side are usually allowed to. Fairly often companies have died not because of lack o innovation from the "makers" within the company, but lack of imagination from the "money bags" of the company, so the non-productive pencilpushers who write the checks, and by doing so control a whole bunch of things they lack basic understanding of. Where I used to work the way that this sort of thing was avoided was by giving the control over classically management type things to techies, like a fairly large proportion of the budget. What this resulted in was a boost in productivity and efficiency that meant that we as a company overall were able to do a lot more with the resources we had, and increase the productivity year by year a lot more while shifting progressively more of the budget from personnel investment to equipment and software, bought and in-house developed. Anyway, I have yet to see AI being able to contribute the kinds of things the techie side can and do contribute continuously, in that AI has yet to demonstrate the type of creativity and innovation that comes from understanding the existing roles of a company in it's industry/market and identifying areas where for example consolidation can bring a bunch of leaps in efficiency and/or expand the roles that a company can take within it's market or segment, or beyond. I would expect a correctly designed and tuned AI to be able to take over some of the roles I am referring to as being done by techies BUT I think we are quite far from where that will actually really become a thing. Mostly because we are not giving AI a chance to, the way that it is being used today - the datasets and datafeeds we are giving AI as well as the roles that we gear them for do not enable them to innovate or contribute on that level. We don't know what AI would be able to contribute on that kind of scale because it has never been tried in a way that it would be what I would consider a "fair shake". The scope given to AI so far has been too narrow, as far as I know. What I mean is that an AI designed for creating automobiles isn't likely to suddenly come up with a spaceship design or a supercomputer architecture, we simply don't know if it could or not, if it had the data and mandate to. - Basically we need a healthy boost shot of imagination, both on the human as well as the AI side. Together we are more than the sum of our parts, and someone will take the step to let the combination loose at some point, with a mandate and resources to go beyond the scope which we have set so far. When that happens something will come out of it, I hope it isn't "Skynet" - my experience does not point that way so far, but it's hard to say for sure.

NLP is the field of Natural Language Processing, LLM uses deep learning to carry out those tasks.

@@jerkooolyes but LLM has no explicit grammar nor explicit semantics

Thanks for the feedback :) While your concerns about the abstract discussion of customer experience and the lack of proven predictions in the video are noted, it’s unfair to say that it doesn’t provide valuable insights into the potential benefits of generative AI. John highlights the increasing demand for AI and digital applications in customer operations and emphasizes the importance for businesses to adapt to this trend while offering valuable considerations for companies looking to implement AI technologies. It's also worth noting that successful implementation of AI requires a holistic approach that considers customer experience, employee engagement, change management, and other factors.

Hmmm yet Elon is advocating for halting development of AI just because it's able to respond in decent English sentences. That to me demonstrates that Elon has no idea what's going on.

​@@boostaiI can't help but feel that this talk sounds more like it would have been timely two years ago rather than 2 months ago. The speaker has not yet caught up too how AI is generating usefulness and value and its deployment options today. He did not understand how private data can be protected and how the API is separated from customer data. I suppose there would be some interest from executives who have no knowledge of AI at all but at the same time I can't let go of the feeling that the speaker is not totally familiar with the AI models he is discussing, let alone able to guide business to deploy, manage, and utilize them. Electrical engineering does not give you the foundation to understand these conversation user interfaces (CUI) perhaps?

Hi Jacob! LLMs and NLU both have their advantages and disadvantages. What we see as the way forward for creating chatbots is a hybrid of both technologies. That way, the generative functionality of LLMs can still be leveraged by businesses without compromising as much on accuracy and reliability.

Exactly what we're going for! Thank you for your kind words.

@@boostai 6up6I6u6u6ul