A structured map of mathematics?
"Your concerns about the arbitrariness of the rules is a valid one."
Money is pouring into the AI industry. Will software survive the disruption it causes?
If velocity is just a tool and not a goal, how do you measure real success for engineering teams?
This post explores crucial lessons learned in the trenches of data licensing, drawing insights from Stack Overflow and the growing importance of socially responsible data practices in a changing internet landscape.
Community “management” at its core is supporting and enabling communities to manage themselves.
You might already be familiar with the programming language best suited to building on blockchains.
Avoiding bad data is just as important in AI; it can open you to fines, lawsuits, and lost customers.
Financial institutions face a balancing act between tech innovation and strict regulations. As customer expectations for improved user experience and demands from those tasked with enhancing features keep rising, engineering teams need to find a harmonious middle ground.
Self-supervised learning is a key advancement that revolutionized natural language processing and generative AI. Here’s how it works and two examples of how it is used to train language models.
An update on recent launches and the upcoming roadmap
Is “agentic AI” just a buzzword, or is it the sea change it seems?
AI is not a linear process. To scale effectively, engineering leaders must account for varied edge cases, presenting a new set of challenges.
As with cars, there are few system administration tasks that involve little to no automation.
In March, over 1,000 developers and technologists gave us insights into what they think about open source and the role it plays with AI.
AI is changing how we think about coding. While tools evolve, critical thinking, problem-solving, and creativity remain the essential skills for top developers.
Data has always been key to LLM success, but it's becoming key to inference-time performance as well.
Efficiently solving a complex scheduling problem using simulated annealing.
Understand the difference between complicated and complex, then simplify and manage complexity.
The new fallacy: argmentum ad robotum.
Til hamingju, Iceland, you've proved the benefits of working less.
Check out an excellent deep dive on what we hope is a patched backdoor.
Network science did a pretty good job of guessing the next pope.
The question is never could we build it; it's should we.
Teaching machines to understand the nuances of spoken language.
When your data set uses a lot of fan fiction, don't be surprised when it treats you like a Mary Sue.
Think of it as near-future science fiction backed by research.
Here's why optimizing code is hard, brute-force work.
AI is coming for everyone who excels at weird niche trivia.
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Every week we’ll share a collection of great questions from our community, news and articles from our blog, and awesome links from around the web.
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