Artificial Inteligence Related Topics 
TechCrunch
NOVEMBER 5, 2023
Kai-Fu Lee, the computer scientist known in the West for his bestseller AI Superpowers and in China for his bets on artificial intelligence unicorns, has a new venture — and a great ambition. AI with the vision to develop a homegrown large language model for the Chinese market. […] © 2023 TechCrunch.
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.
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CIO
DECEMBER 5, 2024
The world must reshape its technology infrastructure to ensure artificial intelligence makes good on its potential as a transformative moment in digital innovation. New technologies, such as generative AI, need huge amounts of processing power that will put electricity grids under tremendous stress and raise sustainability questions.
TechCrunch
JANUARY 4, 2024
2024 is going to be a huge year for the cross-section of generative AI/large foundational models and robotics. There’s a lot of excitement swirling around the potential for various applications, ranging from learning to product design. In a blog post […] © 2023 TechCrunch.
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In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your application’s analytics capabilities?
Martin Fowler
FEBRUARY 13, 2024
LLM engineering involves much more than just prompt design or prompt engineering. Here David Tan and Jessie Wang reflect on how regular engineering practices such as testing and refactoring helped them deliver a prototype LLM application rapidly and reliably.
Martin Fowler
APRIL 13, 2023
His initial prompt primes the LLM with an implementation strategy (chain of thought prompting). A couple of weeks ago I watched a fascinating Zoom call hosted by Xu Hao , Thoughtworks's Head of Technology in China. He showed an example of how he uses ChatGPT to help him code in a self-testing style.
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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.
Advertiser: Data Robot
By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the whitepaper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.
Advertiser: Data Robot
By leveraging the power of automated machine learning, banks have the potential to make data-driven decisions for products, services, and operations. Read the white paper, How Banks Are Winning with AI and Automated Machine Learning, to find out more about how banks are tackling their biggest data science challenges.
Advertiser: Data Robot
But in order to reap the rewards of Intelligent Process Automation, organizations must first educate themselves and prepare for the adoption of IPA. In Data Robot's new ebook, Intelligent Process Automation: Boosting Bots with AI and Machine Learning, we cover important issues related to IPA, including: What is RPA?
Advertiser: Data Robot
Today’s economy is under pressure from inflation, rising interest rates, and disruptions in the global supply chain. As a result, many organizations are seeking new ways to overcome challenges — to be agile and rapidly respond to constant change. We do not know what the future holds.
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?
Advertiser: Data Robot
In March 2020, the world was hit with an unprecedented crisis when the COVID-19 pandemic struck. As the disease tragically took more and more lives, policymakers were confronted with widely divergent predictions of how many more lives might be lost and the best ways to protect people.
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.
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