Remove Artificial Inteligence Remove How To Remove Machine Learning
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Artificial Intelligence in practice

CIO

The world has known the term artificial intelligence for decades. When considering how to work AI into your existing business practices and what solution to use, you must determine whether your goal is to develop, deploy, or consume AI technology. Today, integrating AI into your workflow isn’t hypothetical, it’s MANDATORY.

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5 machine learning essentials nontechnical leaders need to understand

TechCrunch

We’re living in a phenomenal moment for machine learning (ML), what Sonali Sambhus , head of developer and ML platform at Square, describes as “the democratization of ML.” Snehal Kundalkar is the chief technology officer at Valence. She has been leading Silicon Valley firms for the last two decades, including work at Apple and Reddit.

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Leveraging AMPs for machine learning

CIO

It’s hard for any one person or a small team to thoroughly evaluate every tool or model. The problem is that it’s not always clear how to strike a balance between speed and caution when it comes to adopting cutting-edge AI. Yet, today’s data scientists and AI engineers are expected to move quickly and create value.

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Can Artificial Intelligence Replace Human Intelligence?

The Crazy Programmer

Artificial Intelligence is a science of making intelligent and smarter human-like machines that have sparked a debate on Human Intelligence Vs Artificial Intelligence. Will Human Intelligence face an existential crisis? Impacts of Artificial Intelligence on Future Jobs and Economy.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. Download this guide to find out: How to build an end-to-end process of identifying, investigating, and mitigating bias in AI. How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. These autoregressive models can ultimately process anything that can be easily broken down into tokens: image, video, sound and even proteins.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements.

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Data Science Fails: Building AI You Can Trust

The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Download the report to gain insights including: How to watch for bias in AI. How human errors like typos can influence AI findings. Why your organization’s values should be built into your AI.

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The Business Value of MLOps

As machine learning models are put into production and used to make critical business decisions, the primary challenge becomes operation and management of multiple models. Download the report to find out: How enterprises in various industries are using MLOps capabilities.

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How to Choose an AI Vendor

You know you want to invest in artificial intelligence (AI) and machine learning to take full advantage of the wealth of available data at your fingertips. But rapid change, vendor churn, hype and jargon make it increasingly difficult to choose an AI vendor.

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The New Tech Experience: Innovation, Optimization, and Collaboration

Speaker: Paul Weald, Contact Center Innovator

Learn how to streamline productivity and efficiency across your organization with machine learning and artificial intelligence! How you can leverage innovations in technology and machine learning to improve your customer experience and bottom line.

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How AI and ML Can Accelerate and Optimize Software Development and Testing

Speaker: Eran Kinsbruner, Best-Selling Author, TechBeacon Top 30 Test Automation Leader & the Chief Evangelist and Senior Director at Perforce Software

In this session, Eran Kinsbruner will cover recommended areas where artificial intelligence and machine learning can be leveraged. This includes how to: Obtain an overview of existing AI/ML technologies throughout the DevOps pipeline across categories.