How sustainable compute infrastructure supports business growth & opens up an AI advantage
Aging IT infrastructure significantly hampers enterprise growth and competitiveness, particularly in the context of AI and modern business challenges.
Reddit debuts AI-powered discussion search-but will users like it?
Reddit's partnerships with tech firms raise concerns over misinformation and AI accuracy, as users attempt to manipulate public data.
GitHub Copilot code quality claims challenged
The validity of GitHub's claims about Copilot's code quality is challenged due to methodological concerns raised by developer Dan Cîmpianu.
QCon SF 2024 - Why ML Projects Fail to Reach Production
Machine learning projects face severe challenges, with an 85% failure rate primarily due to misalignment with business needs and poor data management.
Author Post: Earth to Google: Your Business Tools Need to Do Better
Technology often feels like a barrier when it fails to provide effective solutions for business problems.
One of China's best GPU prospects admits it's in trouble
Xiangdixian Computing Technology has acknowledged failed GPU development targets, leading to staff layoffs and restructuring efforts amidst market pressures.
AI-Fakes Detection Is Failing Voters in the Global South
Detection models struggle with low-quality media from less represented regions, leading to inaccuracies and potential policy missteps.
The TechBeat: Here's How we Made a Real-time Phishing Website Detector for MacOS (9/2/2024) | HackerNoon
Real-time phishing detection for macOS enhances privacy through on-device alerts without needing cloud solutions.
New RAND Research - Why do AI Projects Fail? - insideAI News
Many AI projects fail due to miscommunication, inadequate data, infrastructure issues, and overly ambitious problem-solving.
Successful AI implementation requires a focus on solving real user problems rather than just deploying new technologies.
American tech workers want AI regulation - but they might have to wait a while
American tech workers support strong regulations for better technology use.
Level AI applies algorithms to contact center pain points | TechCrunch
AI-powered tools by Level AI improve productivity in contact centers by automating tasks and providing insights for both managers and agents.
Generative AI Is Totally Shameless. I Want to Be It
AI has notable challenges like lack of proper attribution, biased outputs, and an obsession with creating a future AI god. Despite issues, its allure remains.
DatologyAI is building tech to automatically curate AI training data sets | TechCrunch
Biases can emerge from massive data sets, hindering AI models.
Data preparation challenges, including cleaning, are significant obstacles for AI initiatives.
This Week in AI: Do shoppers actually want Amazon's GenAI? | TechCrunch
Amazon has announced Rufus, an AI-powered shopping assistant that lives inside its mobile app and helps users find products, perform comparisons, and receive recommendations.
The average person may not be interested in AI chatbots like GenAI, as surveys have shown that a large majority of people do not know about or use them.