The post offers insights into a Deep Learning Course and provides a link to Stanford's machine learning lecture series.
Participants highlight the significance of a strong foundation in linear algebra, probability, calculus, and coding for deep learning and machine learning.
Various resources, including online courses, books, and videos, are recommended to enhance understanding in deep learning, with an emphasis on personal effort and commitment to becoming an expert in ML/DL.
The author discusses common mistakes and bad practices in data visualization, providing examples and explanations for each mistake.
Examples of these mistakes include using bar plots for mean separation, using violin plots for small sample sizes, using bidirectional color scales for unidirectional data, and making bar plot meadows.
The importance of reordering rows and columns in heatmaps, checking for outliers, considering data range at each factor level, trying different layouts for network graphs, and avoiding confusion between position and length-based visualizations are also highlighted.
The author advises against using pie charts or concentric donuts, as well as red/green and rainbow color scales.
The conclusion emphasizes the need to optimize stacked bar plots by reordering the bars.
The article and forum emphasize the significance of creating accurate and informative graphs, while criticizing ineffective heatmaps and data manipulation.
Participants suggest resources such as Edward Tufte's book and John Tukey's paper to improve data visualization skills.
The discussion explores the application of Tufte's principles and the potential for misleading information in graphs, with recommendations for understanding human perception of data and creating effective charts and graphs.
Python 3.12 is deprecating and planning to remove certain functions in the datetime module, which return timezone-less datetime objects, potentially causing problems.
The author recommends using alternative functions due to the debate surrounding the usage of naive or aware datetimes in Python.
Storing datetimes in UTC and keeping timezone information up to date are emphasized as crucial practices, and various participants in the discussion express their opinions and concerns regarding timezone handling in programming languages.
Zero-K is a free real-time strategy game with physics-based units and projectiles, offering over 100 unique units and various gameplay options.
The latest update brings new bombers, unit adjustments, balance changes, and expanded modding capabilities.
Additionally, the update includes fixes and enhancements to gameplay, AI opponents, and modding features, introducing a new control point game mode called Artefact Control. Zero-K strives to be the top-ranked free real-time strategy game.
The article and comment thread compare the RTS games Zero-K and Beyond All Reason (BAR) as successors to Total Annihilation.
They discuss differences in gameplay, economy, and population caps between the two games.
Other topics include turtling strategies, the potential revival of the RTS genre, Zero-K's gameplay, AI, system requirements, game development on Linux, moral implications of war games, and the definition of a game versus a mod.
LoRA (Low-Rank Adaptation) is used to fine-tune custom language models, reducing memory usage and computational resources by decomposing weight changes.
The outcomes of using LoRA are consistent with minimal variation based on optimizer choice, with potential advantages of using SGD over Adam optimizer.
Insights and lessons learned from experiments include the importance of applying LoRA across all layers and efficient fine-tuning of large models with limited GPU memory, as well as considerations around implementing LoRA, dataset impacts, and the potential benefits of using other optimization algorithms.
Kyle Vogt, co-founder and CEO of Cruise, has stepped down from his role.
Mo Elshenawy, the current executive vice president of engineering at Cruise, will assume the position of president and CTO.
The resignation follows the suspension of Cruise's permits by the California Department of Motor Vehicles, stemming from an incident involving a pedestrian and a Cruise robotaxi. Cruise has received criticism for poor management and a lack of emphasis on safety, resulting in low morale and layoffs. Vogt plans to spend time with his family and explore new ventures, while GM underscores the importance of safety and accountability to rebuild public trust.
French billionaire Xavier Niel has unveiled his plans for Kyutai, a nonprofit AI research lab in Paris, focused on artificial general intelligence.
The lab has secured funding of around €300 million ($330 million) from multiple sources, including French billionaire Rodolphe Saadé.
Kyutai has acquired a thousand Nvidia GPUs from Scaleway to meet its computational requirements and has hired a strong scientific team with notable AI researchers as advisors. The lab intends to release open source models, training source code, and data. Additionally, Niel supports the regulation of AI use cases, aligning with France's viewpoint on the European AI Act.
The forum discussion revolves around open-source software, AI models, language learning, starting AI businesses in Europe, and the performance of the AI model Mistral.
Participants share their views on the definition and significance of open source, copyrightability of AI models, language learning, starting AI companies in Europe, and concerns about Mistral's performance.
Funding allocation and advancements in the field of AI are also briefly discussed.