IBM Journey to AI blog

MAY 31, 2023

Register for PrestoCon Day The post Join us at PrestoCon Day, a free virtual community event appeared first on IBM Blog. Why Presto and IBM? At PrestoCon Day, you’ll get to see some of the new features coming to Presto, IBM watsonx.data, as well as learn more about common use cases and best practices.

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IBM Journey to AI blog

DECEMBER 8, 2023

The hybrid cloud approach is complemented by the IBM Edge Application Manager, enabling OEMs to scale and operate edge solutions autonomously, along with the IBM Embedded Automotive Platform, a Java runtime optimized for in-vehicle use.

Automation 168

Automation Data Platform Software Development AI Engineer 168

IBM Journey to AI blog

SEPTEMBER 28, 2023

According to a recent IBV study , 64% of surveyed CEOs face pressure to accelerate adoption of generative AI, and 60% lack a consistent, enterprise-wide method for implementing it. For many businesses and organizations, this can introduce uncertainties that slow adoption of generative AI, particularly in highly regulated industries.

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IBM Journey to AI blog

JULY 27, 2023

” As artificial intelligence reshapes business, Watson’s advice still applies: A recent study by the IBM Institute for Business Value (IBV) finds that 75% of CEOs surveyed believe their competitive advantage will depend on who has the most advanced generative AI. Watson, Sr.,

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IBM Journey to AI blog

AUGUST 1, 2023

We are bringing the power of foundation models with the availability of a GPU as a service on IBM Cloud offering to help organizations tap into artificial intelligence (AI) in a secured environment while aiming to mitigate third- and fourth-party risk.

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IBM Journey to AI blog

JANUARY 10, 2024

Artificial intelligence (AI) refers to the convergent fields of computer and data science focused on building machines with human intelligence to perform tasks that would previously have required a human being. What is artificial intelligence and how does it work?

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IBM Journey to AI blog

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. Most experts categorize it as a powerful, but narrow AI model.

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AWS Machine Learning Blog

AUGUST 4, 2023

We’re excited to announce Amazon SageMaker and Salesforce Data Cloud integration. With this capability, businesses can access their Salesforce data securely with a zero-copy approach using SageMaker and use SageMaker tools to build, train, and deploy AI models.

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IBM Journey to AI blog

JULY 17, 2023

Generative AI has the potential to significantly disrupt customer care, leveraging large language models (LLMs) and deep learning techniques designed to understand complex inquiries and offer to generate more human-like conversational responses. Watsonx.ai

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IBM Journey to AI blog

FEBRUARY 19, 2024

Data monetization empowers organizations to use their data assets and artificial intelligence (AI) capabilities to create tangible economic value. Data products can also be created for wider external consumption across multiple organizations and ecosystems.

Data Platform 159

Data Platform Automation AI Automation Artificial Intelligence 159

IBM Journey to AI blog

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. An LLM like Falcon-40B, offered under an Apache 2.0

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IBM Journey to AI blog

SEPTEMBER 20, 2023

Foundational models (FMs) are marking the beginning of a new era in machine learning (ML) and artificial intelligence (AI) , which is leading to faster development of AI that can be adapted to a wide range of downstream tasks and fine-tuned for an array of applications.

Large Language Models 208

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IBM Journey to AI blog

SEPTEMBER 7, 2023

It’s an exciting time in AI for business. As we apply the technology more widely across areas ranging from customer service to HR to code modernization, artificial intelligence (AI) is helping increasing numbers of us work smarter, not harder. Test out watsonx.ai

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Marktechpost

AUGUST 21, 2023

When combined with data from other sources, including marketing data platforms, Excel may provide invaluable insights quickly. With the advent of AI (artificial intelligence), Excel users no longer need to memorize hundreds of long, winding Excel formulas to enter complex calculations and get thorough insights.

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IBM Journey to AI blog

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? The platform comprises three powerful products: The watsonx.ai

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IBM Journey to AI blog

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. With IBM® watsonx.ai ™ AI studio, developers can manage ML algorithms and processes with ease. What is machine learning?

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AWS Machine Learning Blog

AUGUST 4, 2023

After you create the API, we recommend registering the model endpoint in Salesforce Einstein Studio. For instructions, refer to Bring Your Own AI Models to Salesforce with Einstein Studio The following diagram illustrates the solution architecture. JWT can be used as a part of OpenID Connect (OIDC) and OAuth 2.0

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IBM Journey to AI blog

JUNE 8, 2023

So how do businesses that want to incorporate AI move forward when there is such a high level of difficulty? Krista also plans to continue to deepen its work with IBM, including exploring the upcoming IBM watsonx AI and data platform , to help clients like Zimperium unlock AI’s true potential.

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IBM Journey to AI blog

JULY 17, 2023

The watsonx platform has three components: watsonx.ai (now available), watsonx.data (now available) and watsonx.governance (expected availability in November). In this blog, I will cover: What is watsonx.ai? Each IBM-trained foundation model brings together cutting-edge innovations from IBM Research and the open research community.

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NVIDIA

AUGUST 28, 2023

“It was a ‘wow’ moment because on CPU clusters, it takes more than 48 hours to process just seven days of data — in the past, we had the data but couldn’t use it because it took such a long time to process it,” said Abhay Dabholkar, an AI architect at AT&T, in a blog. “We Learn more in this solution brief.

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IBM Journey to AI blog

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

Together, Principal and AWS have built data ingestion pipelines for customer email interactions and additional metadata from their customer data platform, and built data aggregation and analytics mechanisms to combine omnichannel data into a single customer insight lens.

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IBM Journey to AI blog

JULY 27, 2023

Artificial intelligence is disrupting many different areas of business. According to IBM’s Institute of Business Value (IBV) , AI can contain contact center cases, enhancing customer experience by 70%. Additionally, AI can increase productivity in HR by 40% and in application modernization by 30%.

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IBM Journey to AI blog

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

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The MLOps Blog

MARCH 21, 2023

They work with other users to make sure the data reflects the business problem, the experimentation process is good enough for the business, and the results reflect what would be valuable to the business. A model can be tested against the production model, drawing from the ML metadata and artifact store to make those comparisons.

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AWS Machine Learning Blog

NOVEMBER 27, 2023

SageMaker Canvas also enables you to understand your predictions using feature importance and SHAP values, making it straightforward for you to explain predictions made by ML models. SageMaker Canvas allows you to bring ML models built anywhere and generate predictions directly in SageMaker Canvas.

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