# Sep 6, 2025

## Articles

- **Apertus 70B: Truly Open - Swiss LLM by ETH, EPFL and CSCS**  
  **Apertus-70B-2509** is a new addition to the **Apertus LLM** collection, showcasing advancements in large language models with enhanced capabilities.

- **ML needs a new programming language – Interview with Chris Lattner**  
  **Mojo**, a new programming language by Chris Lattner, aims to enhance GPU programming by combining ease of use with **type-safe metaprogramming**, allowing developers to harness the full power of modern hardware while maintaining productivity.

- **Novel hollow-core optical fiber transmits data 45% faster with record low loss**  
  A **novel hollow-core optical fiber** achieves **45% faster data transmission** with a record low loss of **0.091 dB/km**, surpassing traditional silica fibers which have a minimum loss of **0.14 dB/km**.

- **How big are our embeddings now and why?**  
  **Embedding sizes have significantly increased**, with models like OpenAI's using **1536 dimensions**, reflecting a shift from the previous standard of **300 dimensions** due to advancements in training data and architecture.

- **Now Live: Europe’s First Exascale Supercomputer, JUPITER, Accelerates Climate Research, Neuroscience, Quantum Simulation**  
  **JUPITER**, Europe’s first **exascale supercomputer**, is now operational, enabling unprecedented computational power for scientific research and AI applications.

- **Europe enters the exascale supercomputing league with Jupiter**  
  The **European Commission's Press Corner** serves as a vital hub for accessing official communications, including press releases and statements, enhancing transparency and public engagement. [Link to article](https://ec.europa.eu/commission/presscorner/detail/en/ip_25_2029)

- **[R] The Illusion of Progress: Re-evaluating Hallucination Detection in LLMs**  
  **Current benchmarks for hallucination detection in LLMs are inadequate**, often yielding low-signal results that fail to address real-world high-stakes scenarios, as highlighted in the paper [here](https://arxiv.org/abs/2508.08285).

- **[P] I Was Wrong About Complex ML Solutions - Gower Distance Beat My UMAP Approach**  
  **Gower distance**, a method for calculating distances in mixed categorical and numerical data, often **outperforms complex ML solutions** like UMAP, especially in small-to-medium datasets, highlighting the value of simplicity in machine learning.

- **[P] Knowledge Distillation for Text-to-SQL — Training GPT-2 with Qwen2-7B as Teacher**  
  **Knowledge Distillation (KD)** enables **GPT-2** to effectively generate SQL queries from natural language by learning from the larger **Qwen2-7B** model, demonstrating that smaller models can be trained for specific tasks without the need for massive resources.

- **[D] Baseten raises $150M Series D for inference infra. where’s the real bottleneck?**  
  **Baseten's $150M Series D** emphasizes their commitment to enhancing **inference infrastructure**, targeting low latency and throughput optimization, with a valuation of **$2.1B**.

- **[P] An Open-Source Pipeline for Speech-to-Speech Translation with Voice Preservation (RVC) and Lip-Sync**  
  The project presents an **open-source pipeline** for **speech-to-speech translation** that preserves the speaker's voice and synchronizes lip movements, initially targeting **Telugu** for low-resource language dubbing.

- **Fast 2-Simplicial Attention: Hardware-Efficient Kernels in TLX**  
  **Fast 2-Simplicial Attention** achieves **588 Tensor Core BF16 TFLOPs** with **60% tensor core utilization**, marking a **1.74x speedup** over the original Triton kernel, thanks to a hardware-aligned design and the use of TLX for modern GPU techniques.