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Explainable AI explained
Someday machine learning models may be more ‘glass box‘ than black box. Until then, explainability tools and techniques can help us understand how a black box model makes its decisions.
Review: Google Cloud Vertex AI irons out ML platform wrinkles
Vertex AI greatly improves the integration of Google Cloud’s AI/ML platform and AutoML services, combining a new unified API with very good modeling capabilities.
What is vector search? Better search through AI
Vector similarity search uses machine learning to translate the similarity of text, images, or audio into a vector space, making search faster, more accurate, and more scalable.
Machine learning is moving beyond the hype
Today, companies across every industry are deploying millions of machine learning models across multiple lines of business. Soon every enterprise will take part.
What is AI bias mitigation, and how can it improve AI fairness?
Algorithmic biases that lead to unfair or arbitrary outcomes take many forms. But we also have many strategies and techniques to combat them.
3 ways AI improves CRM
AI has the power to liberate organizations from CRM-related manual processes and improve customer engagement, sales insights, and social networking, for starters.
OpenAI debuts Python-based Triton for GPU-powered machine learning
Triton uses Python’s syntax to compile to GPU-native code, without the complexities of GPU programming.
Design for responsible AI with Microsoft’s HAX
Microsoft Research’s Human-AI eXperience toolkit makes us think about how we use AI in our code.
5 AI startups out to change the world
Deep learning is solving challenging problems in industries as diverse as retail, manufacturing, and agriculture. These companies are leading the way.
How the cloud and big compute are remaking HPC
High-performance computing projects require massive quantities of compute resources. Pairing simulation and specialized hardware with the cloud powers the breakthroughs of the future.
State of AI report finds AI is now core to business success
Appen survey of business leaders and data scientists indicates that AI initiatives are delivering business value but challenges still exist.
5 AI startups leading MLops
From data preparation and training to model deployment and beyond, these companies offer state-of-the-art platforms for managing the entire machine learning lifecycle.
IBM Python toolkit measures AI uncertainty
IBM’s Uncertainty Qualification 360 is an open source library of Python algorithms for quantifying, estimating, and communicating the uncertainty of machine learning models.
3 AI startups revolutionizing NLP
Deep learning has yielded amazing advances in natural language processing. Tap into the latest innovations with Explosion, Huggingface, and John Snow Labs.
How AI can enhance customer experience
G&J Pepsi and Zipline turn to data science and machine learning to get the right products to the right locations at the right time.
Dataiku review: Data science fit for the enterprise
Dataiku’s end-to-end machine learning platform combines visual tools, notebooks, and code to address the needs of data scientists, data engineers, business analysts, and AI consumers.
4 key tests for your AI explainability toolkit
Enterprise-grade explainability solutions provide fundamental transparency into how machine learning models make decisions, as well as broader assessments of model quality and fairness. Is yours up to the job?
8 ways to jump-start your machine learning
From exploratory data analysis to automated machine learning, look to these techniques to get your data science project moving — and to build better models.
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What we just learned about data science — and what’s next
The past 12 months have revealed how valuable data science can be while also exposing its limitations. Expect big advances in the year to come.
