A 20-year professional trader reveals his “money line”
Ditch the indicator and use “MoneyLine”. Simple lines take the guesswork out of knowing when to buy or sell. This is the line on the chart that helped Nic Chahine earn his 83% of option purchases. Here's how he does it.
But amid discussions of new products at this year's conference, it was presentations by outside executives that filled the main ballroom to near capacity on Wednesday. Warren Barclay is responsible for the company's products Vertex AI, GenAI, and Machine Learning. google cloud (NASDAQ:GOOG).
The idea that generative AI could have a major impact on supply chains is not new. But Mr. Barclay depicted how quickly it has already established itself. According to him, GenAI's capabilities are increasing at an exponential level, and real-life impact on supply chain management is either imminent or already in place.
Mr Barclay said that in the real world, where the solution is being implemented, the different estimates of savings and investments in specific industries would be “stunningly vast” and open up a “whole new world”.
Google's AI and machine learning models, which used millions of “parameters” to generate information and solutions just a few years ago, now use trillions of records and are “more efficient than ever before.” It's much bigger,” he said.
The power of context
Barclay said models have the ability to generate “context,” which means that the model can understand certain data even if it is not included in the model or provided by the user. It means. He gave the example of asking a GenAI tool to create an image of an animal that is furry, has a tail, and that humans see as pets. Today, his AI tools can generate an image of the word “cat” even if the model's user doesn't type it.
Barkley said that eventually, GenAI models will increasingly have all the cognitive and sensory abilities of humans except for smell (though he did not mention taste, which is still a GenerativeAI model). It doesn't seem to be included in the toolkit).
He reviewed both the theoretical uses of AI in supply chain management and real-world examples that have already been deployed.
among them:
- A UK customer used AI to determine whether contract language conflicted with Brexit regulations. Without this, this task would have taken an enormous amount of labor time.
- A similar effort is to read California's various government regulations and “try to understand which of them apply to you.”
- A food company used AI to generate standard procurement contracts. This agreement can be used internationally as well as in the United States, as it can read and process data and text from multiple countries.
- “Last year was a proof of concept year,” Barclay said. “A lot of people are experimenting, and more people are actually spending money this year.”
Manhattan Associates unveils its own GenAI
Barkley's talk came after Manhattan Associates announced at the conference that it would add a GenAI solution for customer service to its flagship Manhattan Active product, specifically Manhattan Active Maven, an AI-driven chatbot.
“Maven stands out as the first GenAI-powered customer service chatbot with native access.
Manhattan Associates said Wednesday during the announcement of new products previewed at Momentum by Manhattan Senior Vice President Brian Kinsella.
The company also announced another new product, Manhattan Assist. It's described as “his GenAI-powered assistant that provides contextual answers to all your questions about product features.”
In his speech, Barclay said bots currently used for customer service can only generate responses that “someone has to sit down and write an answer to everything.” With the Gen AI model, that no longer happens. AI generates answers for you so you can predict every question. I think the revolution in how bots are used is huge. ”
He categorized the benefits of AI in business operations into several categories: optimization, automation, streamlining, and transformation.
Although these may overlap in many cases, the most striking was Berkeley's discussion of the term “transformation.'' While the other areas seemed to deal primarily with efficiency, his account of transformation was the most ambitious.
He cited drug development as an example. Generative AI models can analyze how molecules work together much more efficiently and quickly than “million-dollar experts working to actually do it.”
“And we can use these compounds to create new compounds, completely new things that were never thought of before, and we can do it at the speed of light,” Barclay said.
Generative AI also opens the door to personalized marketing, he said. He showed an AI-generated photo of himself with a Texas background. You can also generate similar images to target individual customers. “Marketing plays a very important role when it comes to content generation and how it works,” he said.
Barkley presented a slide that provides guidelines for companies to decide what to do to start an AI solution. Some of the key points sounded like they would be recommended for any technology project in recent history. Prioritize your values and build a team of experts to experiment with your application, collect data, integrate with your existing systems, and scale over time.
Another recommendation is to “do all of this in a reliable state at all times.” He said AI could “hallucinate” on early outputs and produce rough interim outputs, and companies needed to be wary of the damage it could do to their reputations.
Barkley said it's not a good idea to go it alone. “It’s important to find a partner who can work with you to address your challenges and achieve your goals,” he said. “We need partners like that. We're all learning and working at incredible speed.” He cited conference organizer Manhattan Associates as an integrator implementing AI solutions.
Whatever the cost, it has come down significantly, Barclay said. Over the past year, he said, there were times when the cost of implementing an AI solution fell by a factor of 10 and then a factor of 15. At present, the project said he is 40 times cheaper than it was a year ago.
The post-Google executive said FreightWaves first showed the growing use of generative AI in the supply chain.
A 20-year professional trader reveals his “money line”
Ditch the indicator and use “MoneyLine”. Simple lines take the guesswork out of knowing when to buy or sell. This is the line on the chart that helped Nic Chahine earn his 83% of option purchases. Here's how he does it.
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