Why AI Can’t Get Software Testing Right
03/09/2024
It’s already a danger when you write the implementation first; AI is only going to make it worse.
It’s already a danger when you write the implementation first; AI is only going to make it worse.
Python cannot handle two different versions of the same package which leads to “dependency hell”, causing entire installations to fail.
Bython is Python with braces because Python is awesome, but whitespace is awful.
NVIDIA has been using Ubuntu exclusively to demonstrate deep learning on all its edge solutions which suggests Linux performs better
TypeScript’s static typing helps ensure code quality and reduces the likelihood of bugs slipping through to production.
At the root of this issue lie the datasets used to train these AI image models.
Perhaps the most critical challenge that LLM developers face is the lack of robust methods for verifying the outputs of
Most AI image generators today excel at deepfakes yet fail to depict the correct time, often stuck at 10:10.
MAG does not use any positional encodings, which contrasts current trends for GNNs and Transformers.
FLUX.1 AI is one of very few text-to-image models that generate human hands right and it can be locally hosted
If you think protecting private data was hard with databases, LLMs make it even harder.
AI note-taking apps often record and transcribe entire conversations, capturing a lot of potentially sensitive information.
While the JSON-based API can help developers improve the output of their models, with Prolog, models can have better reasoning
The price for manual labelling tasks can range from $0.05 to $0.30 per label.
Nokia is the only firm capable of delivering all key networking components outside of China, positioning it as a pivotal
After ChatGPT restrictions, uncensored LLMs began outperforming aligned models in some tests as ChatGPT’s response quality declined.
Yotta being an elite partner received the first shipment of the 4000 H100s in March 2024.
While mixture of experts is an innovative approach to overcome hardware restrictions, mixture of agents goes one step further in
Nidum.AI plans to use 2000+ Apple computers to run Llama 3.1 on P2P network.
A report suggests that 81% of developers are already using AI-powered coding assistants like ChatGPT and GitHub Copilot.
SIMBA can identify individuals by analysing their voice patterns and facial features.
Fortify Aviator aims to enhance the accuracy of vulnerability detection and provide developers with actionable insights.
Knowledge graphs help reducing AI hallucinations, provides up-to-date information, and leverages the relationships between data points to enhance the quality
Despite U.S. trade restrictions, Huawei has developed Kirin 9000s chip, featuring 7-nanometer processing technology.
MachineHack emerges as the go-to platform for AI/ML professionals, offering hackathons, and assessments to bridge the gap LeetCode can’t fill.
Uncensored LLMs offer unrestricted creativity, enhanced learning, and deeper insights while ensuring privacy.
Deep-ml.com aims to provide a LeetCode-like experience specifically tailored for machine learning enthusiasts and professionals.
A recent report published by Canalys suggests that by the end of 2024, 16% of new smartphones shipped will be
By addressing hardware and software compatibility and ease of usage, AI-driven operating systems can achieve mainstream adoption and transform the
Studies by the McKinsey Global Institute estimate that increasing female workforce participation by just 10% could add a staggering $550
Discover how Cypher 2024 expands to the USA, bridging AI innovation gaps and tackling the challenges of enterprise AI adoption
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