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17 results for “corporate ai limitations”
to the liability management transactions we talked about. Mhmm. So perhaps folks are thinking that that will precipitate. Perhaps it's a reaction to some of the maturity walls that folks understand. Or perhaps it's some of what I was saying in the op
33:44 / 34:50
from transcript33:44 – 34:50
So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need. Now a global workforce of 300,000 can use AI to fill
28:32 / 29:32
from transcript28:32 – 29:32
See complete disclosures at public.com/disclosures. So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrate technology right into the systems they need.
31:30 / 32:31
from transcript31:30 – 32:31
hallucinations in LLMs. The parallel in agents is impersonation. So agents that come along and are essentially impersonating entities, which they don't legitimately represent. And in doing so, taking actions on the behalf of these entities where they
23:15 / 24:17
from transcript23:15 – 24:17
And paid for by Public Holdings, brokered services by Public Investing member FINRA SIPC, advisory services by Public Advisors, SEC registered adviser, crypto services by Xero Hash. Sample prompts are for illustrative purposes only, not investment ad
35:56 / 37:05
from transcript35:56 – 37:05
AI, the the extent of which, like, you know, companies can actually get advantage of AI or, like, improve their processes or, like, you know, streamline the existing processes that they have. I feel it's still in the very early stage. Like, 2025 has
24:02 / 25:09
from transcript24:02 – 25:09
With LLMs, we're starting to get a better understanding. We've had, you know, quite a bit of red teaming exercise and jailbreaking and so on. And so people have identified different risk vectors, prompt injections, things like that, which are vectors
22:29 / 23:33
from transcript22:29 – 23:33
Number two, from there, they start to say, okay. How can I take a process that already exists and apply AI to making it better? That might be, something like customer support or taking fraud down from fifteen days to kinda cure to to ten days. And, l
10:13 / 11:33
from transcript10:13 – 11:33
what you've really got is a a a huge likelihood of a stranded asset out there, natural gas plants that are no longer useful for powering these things that they were built for. The thing about AI for business, it may not automatically fit the way your
34:26 / 35:32
from transcript34:26 – 35:32
All investing involves risk of loss. See complete disclosures at public dot com slash disclosures. So there's a lot of noise about AI, but time's too tight for more promises. So let's talk about results. At IBM, we work with our employees to integrat
30:43 / 31:45
from transcript30:43 – 31:45
Now a global workforce of 300,000 can use AI to fill their HR questions, resolving 94% of common questions. Not noise, proof of how we can help companies get smarter by putting AI where it actually pays off, deep in the work that moves the business.
32:12 / 33:16
from transcript32:12 – 33:16
the return on investment from their AI that they had expected or they had hoped or something like that. Like, does it does it work in some places and not others? Are there industries and functions that are more fit for AI than others, or it's more ab
6:35 / 7:47
from transcript6:35 – 7:47
stay functional and keep delivering value? I think the end goal is for us to to disappear and for the the the AI products and the AI platforms to be fully usable by the business users. Today, this is not the case. Today, this is still too complex. An
18:44 / 19:49
from transcript18:44 – 19:49
...inside of a true corporate enterprise that is not right now a small test. There's not. So where does 6,000,000,000 come from? Because everybody has to show up to their board and have an AI checkbox. And everybody is thousands and thousands of compani
32:14 / 33:15
from transcript32:14 – 33:15
The thing about AI for business, it may not automatically fit the way your business works. At IBM, we've seen this firsthand. But by embedding AI across HR, IT, and procurement processes, we've reduced cost by millions, slashed repetitive tasks, and
36:14 / 37:09
from transcript36:14 – 37:09
And you think this is a tool that was designed twenty plus years ago or has been iterated on for twenty plus years primarily for a human being to write every line of code. When you take a tool like that and you start to introduce AI, you start to int
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from transcript8:55 – 10:07
companies already using Pipedrive. Right now, you'll get a thirty day free trial. No credit card or payment needed. Just head to pipedrive.com/simplecrm to get started. That's pipedrive.com/simplecrm. So there's a lot of noise about AI, but time's to
19:28 / 20:31
from transcript19:28 – 20:31
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