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AGI
4 Real-World AI Projects in the Texas McCombs AI and Machine Learning Program
Learning AI goes beyond algorithms and frameworks. It also means applying them to solve real business challenges. Employers increasingly value…
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Reactive Machines
Progressive Refinement: An Iterative Pseudo-Labeling Approach for Mandarin-English Code-Switching ASR
Self-training has been shown to be helpful in addressing data scarcity for many domains, including vision, speech, and language. Specifically,…
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Reactive Machines
Scaling Laws for Mixture Pretraining Under Data Constraints
As language models scale, the amount of data they require grows – yet many target data sources, such as low-resource…
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Self Aware
Artist and Philosopher Rockwell Kent’s Century-Old Meditations on Art and Life During Seven Months on a Small Alaskan Island – The Marginalian
Not often — a handful of times in a lifetime, if you are lucky — you come upon a work…
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Self Aware
The Difference Between Simplicity and Minimalism
The Difference Between Simplicity and Minimalism – Be More with Less Get your FREE copy of The Simplicity Quick…
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Reactive Machines
Domain and publish date filters for Web Search on AgentCore
When an AI agent uses Web Search to ground its answers on behalf of a customer, the organization behind that…
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Reactive Machines
How Fanatics Betting and Gaming built a multi-agent customer support system
Fanatics Betting and Gaming (FBG) built a multi-agent customer support system on AWS to solve a challenge unique to sports…
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ANI
How to Answer AI System Design Interview Questions
For years, system design interviews meant “Design YouTube,” “Design Uber,” or “Design WhatsApp.” Companies hiring AI Engineers, Applied Scientists,…
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ANI
5 Tools for Building and Deploying AI Agents in Production
Building an agent that works in a notebook takes an afternoon. Getting that same agent to survive real traffic,…
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Self Aware
Moonlight and the Magic of the Unnecessary – The Marginalian
Every night, for every human being that ever was and ever will be, the Moon rises to remind us how…
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