Artificial Intelligence
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Addressing AI hallucinations with retrieval-augmented generation
The hallucinations of large language models are mainly a result of deficiencies in the dataset and training. These can be mitigated with retrieval-augmented generation and real-time data.
BI meets data science in Microsoft Fabric
Microsoft’s cloud-hosted data lake and lakehouse platform gains new data science tools and opens up Power BI datasets to Python, R, and SparkSQL.
AI will remake data centers, OCP says
Open Compute Project expects the hardware requirements of AI to usher in a new era of larger data centers, liquid-cooled hardware, and greater power consumption.
Review: 7 Python IDEs compared
What's the best IDE for Python? Here's how IDLE, Komodo, PyCharm, PyDev, Microsoft's Python and Python Tools extensions for Visual Studio Code, and Spyder stack up.
How to use Google’s PaLM 2 API with LangChain
The advantages of LangChain are clean and simple code and the ability to swap models with minimal changes. Let’s try LangChain with the PaLM 2 large language model.
Best practices for operating cloud-based generative AI systems
From system design to daily performance tuning, here's a checklist of ways to make your systems run effectively.
Making sure open source doesn’t fail AI
The lessons learned from cloud are spurring a proactive examination of what it means to be 'open source' in the rapidly evolving world of AI.
6 ways automation bites software developers
The dream of fully automated development is getting more real by the day, but is that a good thing? Beware of these six gotchas.
Democratizing AI with digital adoption platforms
Digital adoption platforms learn application usage patterns and user behaviors and walk workers through business processes in real time, offering guidance and automating tasks. They can help all of us get the most from AI.
Google indemnifies generative AI customers over IP rights claims
The indemnities include protection against infringement claims over training data used and output generated by Google’s homegrown generative AI capabilities.
Generative AI and migrations to the public cloud
GenAI can analyze application dependencies, network configurations, and security risks, but it will mostly help lazy companies that aren't doing this anyway.
What is LangSmith? Tracing and debugging for LLMs
Use LangSmith to debug, test, evaluate, and monitor chains and intelligent agents in LangChain and other LLM applications.
Google Vertex AI Search updated with healthcare and life sciences capabilities
The company said the new capabilities will help companies find accurate clinical information more efficiently and ask questions about patient records.
How knowledge graphs improve generative AI
Large language models have immense potential, but also major shortcomings. Knowledge graphs make LLMs more accurate, transparent, and explainable.
Docker ties up with Neo4j, LangChain, and Ollama to launch Gen AI Stack
Gen AI Stack, which also comes with a built-in assistant, is expected to accelerate developer tasks within Docker.
Amazon Bedrock generative AI service reaches GA
Serverless managed service offers foundation models for building generative AI applications from several leading AI companies including Anthropic, Cohere, and Meta.
What does generative AI mean for software companies?
AI and machine learning will boost the creativity and problem-solving abilities of software developers. It will also establish a new oligopoly over the software industry.
