Helping Enterprises Responsibly Deploy AI
databricks
JUNE 29, 2023
The promise of artificial intelligence (AI) is undeniable, but its enormous potential also comes with enormous responsibilities. Companies and organizations around the world.
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IBM and TechD partner to securely share data and power insights with gen AI
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Balancing AI: Do good and avoid harm
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Data is essential: Building an effective generative AI marketing strategy
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4 ways generative AI addresses manufacturing challenges
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Enterprises’ best bet for the future: Securing generative AI
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IBM and AWS study: Less than 25% of current generative AI projects are being secured The enterprise world has long operated on the notion that trust is the currency of good business. But as AI transforms and redefines how businesses operate and how customers interact with them, trust in technology must be built.
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Unlocking Innovation: AWS and Anthropic push the boundaries of generative AI together
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Amazon Bedrock is the best place to build and scale generative AI applications with large language models (LLM) and other foundation models (FMs). It enables customers to leverage a variety of high-performing FMs, such as the Claude family of models by Anthropic, to build custom generative AI applications.
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Foundational data protection for enterprise LLM acceleration with Protopia AI
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IBM watsonx Assistant: Driving generative AI innovation with Conversational Search
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Generative AI has taken the business world by storm. Organizations around the world are trying to understand the best way to harness these exciting new developments in AI while balancing the inherent risks of using these models in an enterprise context at scale. These search engines are reliant on keywords and human feedback.
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How the Masters uses watsonx to manage its AI lifecycle
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Bring light to the black box
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Accenture creates a Knowledge Assist solution using generative AI services on AWS
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Enterprises today face major challenges when it comes to using their information and knowledge bases for both internal and external business operations. Although enterprise knowledge bases have, over time, improved the customer experience, they can still be cumbersome and difficult to use.
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The dynamic forces behind data center re-transformation
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IDC predicts a surge in AI-enabled automation , reducing the need for human operations intervention by 70% by 2027 However, AI is also a disruptor, necessitating advanced infrastructure to meet data-intensive computational demands.
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Watsonx: a game changer for embedding generative AI into commercial solutions
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IBM watsonx is changing the game for enterprises of all shapes and sizes, making it easy for them to embed generative AI into their operations. Watsonx is comprised of three components that empower businesses to customize their AI solutions: watsonx.ai Let’s explore a few AI use cases that span different industries.
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Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. ” Are foundation models trustworthy?
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Conversational AI use cases for enterprises
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Author(s): Towards AI Editorial Team Originally published on Towards AI. What happened this week in AI by Louie This week, we were again watching developments in AI-powered robots and LLMs. Perhaps the US AI chip export ban to China is having some impact on driving focus on innovations and efficiency!
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“Organizations are responsible for ensuring that AI projects they develop, deploy or use do not have negative ethical consequences,” as per Gartner. Yet while 79% of executives say AI ethics is important to their enterprise-wide AI approach , less than 25% have operationalized ethics governance principles.
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Candice Vu April 1, 2024 - 10:43pm Sanjeev Verma Product Management Senior Manager In today's data and AI-driven world, it’s important to have the right tools to navigate and analyze vast data sources. Before Data Connect, IT teams or Tableau admins were responsible for deploying, managing, and maintaining Bridge.
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Generative AI that’s tailored for your business needs with watsonx.ai
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Retailers can tap into generative AI to enhance support for customers and employees
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As the retail industry witnesses a shift towards a more digital, on-demand consumer base, AI is becoming the secret weapon for retailers to better understand and cater to this evolving consumer behavior. Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content.
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Modernized applications are deployed, monitored and maintained, with ongoing iterations to keep pace with technology and business advancements. Many enterprises are realizing that moving to cloud is not giving them the desired value nor agility/speed beyond basic platform-level automation.
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How LotteON built a personalized recommendation system using Amazon SageMaker and MLOps
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When training is complete (through the Lambda step), the deployed model is updated to the SageMaker endpoint. The EMR preprocessing batch runs through Airflow according to the specified schedule. The EMR preprocessing batch runs through Airflow according to the specified schedule.
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The future of application delivery starts with modernization
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Where and how these applications are deployed will impact time to market and value realization. The reality is that application landscapes are complex, and they challenge enterprises to maintain and modernize existing infrastructure, while delivering new cloud-native features. How can you realise value from your innovation sooner?
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Generative AI and resilient hybrid cloud systems
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As enterprises invest their time and money into digitally transforming their business operations, and move more of their workloads to cloud platforms, their overall systems organically become largely hybrid by design. Most enterprises have invested heavily in technology transformation but not so much on talent transformation.
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hereafter as Shuto Technology) to help a joint venture Original Equipment Manufacturer (OEM) in China to obtain information in an accurate and cost-effective way for on-site technicians. IBM® recently announced that it has worked with its business partner, Beijing Shuto Technology Co.,
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What Is Retrieval-Augmented Generation?
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To understand the latest advance in generative AI , imagine a courtroom. The court clerk of AI is a process called retrieval-augmented generation, or RAG for short. Retrieval-augmented generation is a technique for enhancing the accuracy and reliability of generative AI models with facts fetched from external sources.
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