Language model applications (LLMs) are released frequently, each promising its own specific speed, cost, and quality advantages. But selecting the best model can be challenging due to the constant influx of new options, manual signups and custom benchmarks, and for some, the output quality and speed are less than satisfactory. In response to these constraints,…
Modern software development can be a complex venture, requiring skills in managing large codebases, verifying code accuracy, maintaining vast documentation, and enhancing performance. All of these tasks demand considerable effort and time from developers. While there are traditional code editors and integrated development environments (IDEs) that offer basic features like syntax highlighting, error detection, and…
In June 2024, AI organization Databricks made three major announcements, capturing attention in the data science and engineering sectors. The company introduced advancements set to streamline user experience, improve data management, and facilitate data engineering workflows.
The first significant development is the new generation of Databricks Notebooks. With its focus on data-focused authoring, the Notebook…
Topological Deep Learning (TDL) has advanced beyond traditional Graph Neural Networks (GNNs) by modeling complex multi-way relationships, which is imperative for understanding complex systems like social networks and protein interactions. A key subset of TDL, known as Topological Neural Networks (TNNs), are proficient at handling higher-order relational data and have demonstrated superior performance in various…
Artificial intelligence (AI) with large language models (LLMs) have made major strides in several sophisticated applications, yet struggle with tasks that require complex, multi-step reasoning such as solving mathematical problems. Improving their reasoning abilities is vital for improving their efficiency on such tasks. LLMs often fail when dealing with tasks requiring logical steps and intermediate-step…