dida is pushing to bring AI-powered software solutions to the broad industry. On twitter, we'll share learnings from our involvement with leading edge research.
In our last reading group, dida’s Machine Learning Scientists discussed the paper (https://t.co/QCT1XCYlrF) from deepseek about the DeepSeek-R1 model and their approach of using reinforcement learning directly without prior fine-tuning.
OpenAI’s new o1 model boosts accuracy with chain-of-thought reasoning, excelling in complex tasks like IMO challenges (83% vs. 13% for GPT-4o) and competitive programming.
Here you can read our summary for the o1 model: https://t.co/ZWhzSTs6kl
#AI#OpenAI#ML#innovation
NVIDIA Shrinks LLama3.1 8B to 4B with Pruning and Distillation
NVIDIA's latest research reduces LLama3.1 8B to 4B parameters by pruning 50% of its layers. Retrained with 40x fewer tokens, the model sees a 16% MMLU score boost. Read more: https://t.co/1G8aEupyx5
#AI#research
We would like to present a paper on Physics-Informed Neural Networks (PINNs) that use physical laws to improve neural network training. It features a recent PyTorch implementation demonstrating PINNs by calculating gravity from thrown ball data.
https://t.co/LJb5bGuzpY
#ML
We recently examined MambaVision, a new backbone combining Vision Transformers (ViT) with Mamba. This integration boosts scores and performance for tasks like object detection and instance segmentation.
More details here: https://t.co/sUiYZxbhBx
#machinelearning#tech#ML#AI
Choosing the Right GPT Model for Your Business
For processing 4,500 documents per month:
◾ It could either spend 126 EUR for the overall task or up to 7.150 EUR
◾ GPT-3.5 is 50 times cheaper than GPT-4
◾ GPT-4o is still 5 times cheaper than GPT-4
#AI#LLM#GPT#TECH4ALL
@GoogleCloud_DE just published a success story about our machine learning project, we did for @enpal_de. Read the full story on their blog - it's about detecting rooftops from satellite data.
Das Greentech @Enpal_de hat mithilfe von @dida_ML, deren abstraktem mathematischen Ansatz zu komplexen #ML-Modellen und Google Cloud den Vertriebsprozess seiner Solarmodule um 87% beschleunigt, Kosten gesenkt und die Kundenerfahrung optimiert. https://t.co/vqlneVZ9x1
On my way to #ICLR2024. I'm looking forward to interesting discussions. Let me know if you're up for a coffee!
Wed: Fast and unified path gradient estimators for normalizing flows (https://t.co/bWsxrM6hJm)
Thu: Improved sampling via learned diffusions (https://t.co/TlgLgsDRFh)
We are thrilled to announce the launch of our brand-new website design!
We aimed to create a user-friendly, informative, and visually appealing platform for our blog readers, customers, and partners.
Take a look at our new website design at https://t.co/JtEX9DHTac
This week in our reading group we covered #BYOL
A very unusual form of self-supervised learning that seems to learn reasonable representations almost from nothing!
𝐆𝐢𝐭𝐇𝐮𝐛 𝐒𝐨𝐮𝐫𝐜𝐞 𝐂𝐨𝐝𝐞: https://t.co/flrGRGDkg5
𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐏𝐚𝐩𝐞𝐫: https://t.co/4sTaXik6Zu
Follow us on X for more interesting #ML papers that you can practically apply to your projects.
https://t.co/5gRK5nE9iB
The network's code and trained weights are publicly accessible, signaling its readiness for integration and further exploration in various real-world applications. #AI
Celebrating 5 years with the dida-conference!🎂
We had an amazing day filled with machine learning (#ML) talks, panels, and workshops featuring top organizations.
We captured some moments of it and turned them into a short video.
𝐯𝐢𝐝𝐞𝐨: https://t.co/JiD02FngFR