Artificial Inteligence Artificial Intelligence Machine Learning 
CIO
NOVEMBER 1, 2024
The world has known the term artificial intelligence for decades. Developing AI When most people think about artificial intelligence, they likely imagine a coder hunched over their workstation developing AI models. Today, integrating AI into your workflow isn’t hypothetical, it’s MANDATORY.
The Crazy Programmer
DECEMBER 25, 2021
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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TechCrunch
AUGUST 25, 2021
Meet Taktile , a new startup that is working on a machine learning platform for financial services companies. This isn’t the first company that wants to leverage machine learning for financial products. They could use that data to train new models and roll out machine learning applications.
CEO Insider
NOVEMBER 15, 2024
To build a successful career in AI vision, aspiring professionals need expertise in programming, machine learning, data analytics, and computer vision algorithms, along with hands-on experience solving real-world problems. Copyright CEOWORLD magazine 2023.
Advertiser: Data Robot
Many organizations are dipping their toes into machine learning and artificial intelligence (AI). Download this comprehensive guide to learn: What is MLOps? How can MLOps tools deliver trusted, scalable, and secure infrastructure for machine learning projects? Why do AI-driven organizations need it?
TechCrunch
MAY 10, 2022
Adam Oliner, co-founder and CEO of Graft used to run machine learning at Slack, where he helped build the company’s internal artificial intelligence infrastructure. With a small team, he could only build what he called a “miniature” solution in comparison to the web scale counterparts.
TechCrunch
NOVEMBER 16, 2021
Machine learning is exploding, and so are the number of models out there for developers to choose from. While Google can help, it’s not really designed as a model search engine. working on machine learning projects, where they saw the kinds of research challenges they are attempting to fix with CatalyzeX.
Advertiser: Data Robot
With the number of available data science roles increasing by a staggering 650% since 2012, organizations are clearly looking for professionals who have the right combination of computer science, modeling, mathematics, and business skills. Fostering collaboration between DevOps and machine learning operations (MLOps) teams.
Advertiser: Data Robot
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.
Advertiser: Data Robot
The risk of bias in artificial intelligence (AI) has been the source of much concern and debate. How to choose the appropriate fairness and bias metrics to prioritize for your machine learning models. How to successfully navigate the bias versus accuracy trade-off for final model selection and much more.
Advertiser: Data Robot
The game-changing potential of artificial intelligence (AI) and machine learning is well-documented. Any organization that is considering adopting AI at their organization must first be willing to trust in AI technology.
Advertiser: Data Robot
While everyone is talking about machine learning and artificial intelligence (AI), how are organizations actually using this technology to derive business value? This white paper covers: What’s new in machine learning and AI.
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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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
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. With new AI and ML algorithms spanning development, code reviews, unit testing, test authoring, and AIOps, teams can boost their productivity and deliver better software faster.
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