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Latest World News Update > Blog > Business > AI demands hit a tipping point: Morgan Stanley Summit – World News Network
Business

AI demands hit a tipping point: Morgan Stanley Summit – World News Network

worldnewsnetwork By worldnewsnetwork Last updated: April 4, 2024 5 Min Read
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New Delhi [India], April 4 (ANI): At the Morgan Stanley Technology, Media & Telecom Conference in San Francisco, the industry’s biggest companies and investors discuss opportunities in chips, software and data from the mass uptake of accelerated computing and generative AI.
CEOs who attended the summit were of the view that traditional and generative AI solutions for potential cost savings and productivity should look for technology companies to provide solutions.
To fuel future growth investors are analysing the strong run up in chip designing and manufacturing for revenue growth and potential tailwinds in data centres need.
Investors are also eyeing AI software companies who are disrupting customer services, marketing and general productivity work flows.
Generative artificial intelligence has moved from platform shift to meeting mass demand from companies to harness deep learning with efficiency, productivity and profitability.
Over 1600 industry investors and senior executives of over 350 companies attended the Morgan Stanley’s Technology Media and Telecom conference in San Francisco. A figure of USD 3 trillion of investment on AI between 2023 and 2027 is quoted during the conference.
Though cost savings and operational efficiencies remain a priority for large enterprises, they are ready to invest on generative AI and traditional AI hardware and software which may reduce cost and increase productivity and revenue in future.
The conference also discussed investments in Semiconductor and future growth. Demand for advanced AI chips with improved design will be makers for future growth.
“Semiconductors are central to facilitating generative AI across industries, and companies are racing to bring next-generation products and end-to-end solutions to market, to address their customers proliferating needs around accelerating computing” said Bill Frauenhofer Head of West Coast Technology Investment Banking at Morgan Stanley.
Semiconductor companies see potential growth from demand from data centres, partnerships with Hyberscalers (large cloud service providers), Sovereigns (private sector companies from healthcare, auto etc sectors), ramp up inference computing companies, advanced packaging and internet of things companies.
“At the conference, software executives shared that their cost-conscious customers have appetite for AI products because they can see potential benefits for savings and productivity, but that they are eager to see a quick return on investment,” said Melissa Knox, Global Head of Software Investment Banking at Morgan Stanley.
The conference revealed some of the biggest trends in AI software, it includes automation in customer services like AI powered chatbots.
Generative AIs advancements now enable chatbots to train and produce multimodal content that includes images and videos. Banks are using generative AI to save time and money on tasks like language translations and written summaries.
Big data is at the heart of generative AIs future, this will help big data companies shaping to mane enterprises, store and deploy their vast information buckets.
“Investors are trying to determine which big data companies will gain and lose market share, as some customers may want to pare down their software and double down on a few data partners because of potential cost and security benefits,” said Brittany Skoda, Global Head of Software Investment Banking at Morgan Stanley.
Skoda added, “While best-of-breeds could move faster and be more specialized, customers are also looking for how unified platforms can help them reduce cloud usage and heighten visibility and control of security protocols.”
In addition, big data companies shared trends in solutions, which they are working for enterprise clients. It includes labelling data to add context or meaning, before they are added to AI models.
Companies said large amount of raw and unlabelled data are held by corporates can become very useful to AI models. Big companies are also working on real time data streaming to improve service and profitability. (ANI)

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