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As AI becomes increasingly embedded in our daily lives, industry leaders and experts are forecasting a transformative 2025. From groundbreaking developments to existential challenges, AIs evolution will continue to shape industries, change workflows, and spark deeper conversations about its implications.
Alibaba Cloud has expanded its AI portfolio for global customers with a raft of new models, platform enhancements, and Software-as-a-Service (SaaS) tools. The announcements, made during its Spring Launch 2025 online event, underscore the drive by Alibaba to accelerate AI innovation and adoption on a global scale.
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Just as supply chain disruptions became the frequent subject of boardroom discussions in 2020, GenerativeAI quickly became the hot topic of 2023. Supply chains are, to a certain extent, well suited for the applications of generativeAI, given they function on and generate massive amounts of data.
AI tools like ChatGPT are grabbing headlines, but other AI techniques and tools specifically designed for enterprises are quietly helping companies meet their sustainability goals. Classic AI is already being used widely today in various use cases, and generativeAI is evolving rapidly to address new classes of use cases.
Implementing generativeAI can seem like a chicken-and-egg conundrum. In a recent IBM Institute for Business Value survey, 64% of CEOs said they needed to modernize apps before they could use generativeAI. From our perspective, the debate over architecture is over.
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Organizations are facing ever-increasing requirements for sustainability goals alongside environmental, social, and governance (ESG) practices. This post serves as a starting point for any executive seeking to navigate the intersection of generative artificial intelligence (generativeAI) and sustainability.
Raj Bakhru , Co-founder and CEO of BlueFlame AI, draws on a wide-ranging background encompassing sales, marketing, software development, corporate growth, and business management. BlueFlame AI offers an AI-native, purpose-built, and LLM-agnostic solution designed for alternative investment managers. He holds a B.S.
Data monetization is a business capability where an organization can create and realize value from data and artificial intelligence (AI) assets. Advanced data management software and generativeAI can accelerate the creation of a platform capability for scalable delivery of enterprise ready data and AI products.
Robots and drones perform inspections by using AI-based visual recognition techniques. Sensoring and monitoring also contribute to the direct measurement of sustainability environmental, social and governance (ESG) metrics such as energy efficiency and greenhouse gas emission or wastewater flows.
Across industries, the exponential growth of technologies such as hybrid cloud, data and analytics, AI and IoT have reshaped the way businesses operate and heightened customer expectations. Businesses are now entering an even greater digital era marked by broader applications of AI, including generativeAI models.
According to a recent IBM Institute for Business Value survey, 95% of surveyed global executives say their organizations have developed ESG propositions. However, many of these organizations lack a clear pathway to realizing their goals and 41% of surveyed executives cite inadequate data as their biggest obstacle to ESG progress.
“MVI’s AI-powered visual inspection and modeling capabilities allow for head- and tusk-related image recognition of individual elephants similar to the way we identify humans via fingerprints,” explained Kendra DeKeyrel, Vice President ESG and Asset Management Product Leader at IBM.
The grid itself must green to operate within the environmental, social and governance (ESG) objectives and become carbon neutral by 2050. New emerging technology enables AI-powered digital twins to operate the smart grid. However, operators must balance intermittent renewable energy intake to produce a controlled, stable output.
With growing interest in generativeAI after the release of OpenAI’s ChatGPT in November last year, agencies are now laying the groundwork for AI-based initiatives both on the enterprise and client side. We believe in AI as a business enablement tool,” Gardner said.
Integrating artificial intelligence (AI) within the finance sector has catalyzed a transformative shift, offering unprecedented efficiency, security, and user experience enhancements. Let’s delve into more detail about a few firms utilizing AI in finance, showcasing their innovative approaches and the impact of their contributions.
GenerativeAI is expected to be the most influential trend permeating the entire financial services sector of 2024. Listen: The Art of AI featuring a Financial Industry perspective with Citigroup Trend: GenerativeAI One of the, if not the, biggest technological advancements made in 2023 was generativeAI.
IBM has been hard at work utilizing innovations in artificial intelligence and generativeAI to help organizations find solutions to accelerate sustainability efforts — including several that debuted at Climate Week NYC earlier this week. What role can AI play in improving resiliency?
Cohere’s multilingual embedding model Cohere is a leading enterprise AI platform that builds world-class large language models (LLMs) and LLM-powered solutions that allow computers to search, capture meaning, and converse in text. They provide ease of use and strong security and privacy controls. . How about a query in Danish?
needed to address some of these challenges in one of their many AI use cases built on AWS. Amazon Bedrock Amazon Bedrock is a fully managed service that offers a choice of high-performing FMs from leading companies, including AI21 Labs, Anthropic, Cohere, Meta, Stability AI, and Amazon.
Check out more of the talks and workshops from industry-leading data science and AI organizations coming to ODSC East 2023 below. Through real-world use cases, you’ll explore the ways Knowledge Graphs can enable a more intelligent, knowledge-aware conversational AI. It’s time for part 2 of our partner session highlight.
When I talk to corporate customers, there is often this idea that AI, while powerful, wont give any company a lasting competitive edge. Indeed, maybe one day, when businesses and markets are driven by the invisible hand of AI, the equal-opportunity hypothesis might ring true. this article for an in-depth introduction).
Artificial intelligence (AI) in supply chains is a chicken-or-the-egg thing. There are those who extol AI for its potential to create greater visibility into supply chain operations. In other words, AI first, visibility second. Second, GenAI and other AI tools can help build a bridge toward greater supply chain automation.
But one topic still seems to be front and center on everyones mindartificial intelligence (AI)/generativeAI (GenAI). It is the age of innovation FOMO, and leaders are overwhelmingly being asked to incorporate some AI/GenAI functionality into their operations so their companies are not left behind.
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