This is the second in our interview series with HPC and AI Senior Solutions Architect at Dell Technologies Bottier Bottier. He discusses AI in the workplace, prediction technology and more. With his Network and System security background, he has worked with startups and multinational corporations. Bottier is also a subject matter expert in artificial intelligence, storage, security, networks and big data.
In the second of the Two-Part Interview with Bottier.
Join us as we delve into the fascinating developments in AI in the workplace as well as the world of Dell Technologies!
TT: How do you think AI will impact the workplace of the future and the tech industry in general?
Bottier: AI is already impacting the workplace. It’s not ‘will be’ anymore, it’s already happening. In tech, AI has been impacting the way we recruit people, the way we deal with talent internally, and has also been embedded into products that we use and sell.
There are more tools coming up in AI that we are being highly cautious about. As an example, while Chat GPT is an interesting tool, many competitors are coming up on both the company and country levels. At the country level, France, China and Singapore, all of them are reportedly building their own. So, those tools will be there and impact our professional and personal lives. However, from a corporate perspective, we would be very careful using it for privacy and data security concerns and thus will probably increase the time for proper adoption.
TT: Can you throw some light on the AI-related products & offerings from Dell Technologies?
Bottier: When we talk about AI, it’s not so much about a product per se. AI is more of a new practice of learning from data. We have data, we try to learn from the data to gain new insight, detect new patterns that we can use to make predictions. So, when it comes to a product, it’s typically a combination of hardware and software. It will have infrastructure, servers, storage, networking and accelerators, alongside some softwares that will facilitate data ingestion, data processing, and generate a way to be able to query for prediction.
Then, this technology has a range of products around the field, from small scale to large scale. At Dell, we have a set of such products that are built on AI.
TT: How does Dell approach prediction technology in terms of machine learning?
Romain: Prediction in traditional machine learning and deep learning can be done completely from scratch for us at Dell. We have some of our data scientists that are actually developing their own stuff without using third party softwares. That’s what data scientists do. Now, having said that, we do have a lot of third party partners that develop products specifically to simplify the process of getting data in from multiple sources. It could be Log files, Excel files or data from the cloud.
Find what type of data it is, process it to make it easier for training purposes and they will build the prediction technology for you. That’s what we call auto machine learning. So we also work with this type of tool. Depending on the customer experience with artificial intelligence, it can be from scratch to a fully automated solution.
TT: Can you give us an example of how IoT is used in Dell? Or maybe your industry?
Romain: For us, IoT is definitely used in manufacturing to optimise the process, for example, predictive maintenance, temperature sensors, voltage sensors and pressure. IoT helps us detect potential problems in our manufacturing chain. We also use IoT for sales forecasting, as you can’t just limit yourself to sales information from people anymore.
Essentially, we can generate more accurate forecasts by combining data from our own softwares as well as market data obtained from various platforms. All this data is used to have a better understanding of where the market is going and what might be needed to achieve optimization.
TT: Are you using any AI tools at the moment?
Romain: We do use AI tools within our business, mainly toward sales purposes as it helps us to understand sales targets. It’s also being used for marketing to understand the type of people we want to target. I can’t particularly name the tools that we are developing internally. We definitely use third party softwares to simplify some of the areas, but our data scientists typically tend to build our tools in-house.
The new and large language chatbots are going to be more in use when they have been adapted for the enterprise. These models can help us simplify the way we write proposals or the way we design solutions, for example.
TT: With the blurring lines of privacy on our devices and the platforms we use, what advice would you give our readers about using social media while being safe?
There are certain people who feel positive about the recommendations and the algorithm under the pretence that it’s good for them to be connected to what they want. And that’s the thing with social media. The question is, how do you know that’s good for you? How do you know the content that you’re getting is good for you? Is it because you feel like it or because it keeps coming at you? There’s a very thin line here. We have access to a lot of information and the content is directed based on a lot of factors. And the one who pulls the content somehow decides more than you as an individual what content you watch.
So that’s why. Giving too much information probably allows businesses to know you too much. So I will say again, be cautious with the data you share. There has been a recent trend of doxing and data brokers as well. When you use a service and you don’t pay for it, then the revenue has to come from somewhere else. So your data is very valuable as an individual. If the businesses don’t sell a product to you, they will probably sell the data to someone else as a product.
OK. That has nothing to do with my activity in my company, but that’s the sad reality when it comes to data analytics and artificial intelligence.
Disclaimer
The opinions expressed within this interview are the personal opinions of the interviewee. The facts & statistics, the work profile details shared by the protagonist/ protagonists do not reflect the views of TechThirsty or its Journalist. Neither TechThirsty nor the Journalist hold any responsibility or liability for the same.
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