AI

def make_rag_chunks(rows, max_chars=700): chunks = [] for row in rows: text = ( row.get(“text_preview”) or row.get(“rendered_text”) or row.get(“description”) or “” ) text = normalize_text(text) if not text: continue sentences = re.split(r”(?<=[.!?])s+”, text) current = “” for sentence in sentences: if len(current) + len(sentence) + 1 <= max_chars: current = (current + ” ” + sentence).strip() … Read more

Nous Research has added a Blank Slate setup mode to the open source Hermes Agent. It transforms the ordinary ride. Instead of a fully loaded default, you start with almost nothing. Hermes Agent is a self-developing agent framework from Nous Research. It works with your device. The team announced a new mode in X. Blank … Read more

TLDR YaFF is the Yandex open-source zero-copy wire format for Protobuf — Apache 2.0, currently C++, v0.1.0. The .proto file is always the source of truth; only the physical memory structure changes. In Yandex benchmarks, Flat Layout reads hot data ~3.8× faster than FlatBuffers, within 1.2× of raw C++ layout. Four architectures – Fixed, Flat, … Read more

NVIDIA Research has released SpatialClaw, a free spatial reasoning training framework. It points to persistent weaknesses in visual language models (VLMs). These models still struggle to judge where objects are, how they relate to each other, and how they move in 3D. SpatialClaw does not retrain the model. Instead, it changes the action interface the … Read more

This week, Liquid AI released two new recovery models. That’s right LFM2.5-ColBERT-350M again LFM2.5-Embedding-350M. Both hold 350M parameters. Both are the first two members of the LFM family. They build on LFM2.5-350M-Basewhich was released in March. This pairing is aimed at fast multilingual and cross-linguistic searches in all 11 languages. Their footprint is small enough … Read more

def extract_function_source(full_text, function_name): text = full_text.replace(“rn”, “n”) fence = re.search(r”“`(?:python)?n(.*?)“`”, text, flags=re.S | re.I) if fence: text = fence.group(1) pattern = rf”^defs+{re.escape(function_name)}s*(” match = re.search(pattern, text, flags=re.M) if not match: return “” chunk = text[match.start():] lines = chunk.splitlines() collected = [] for i, line in enumerate(lines): if i > 0: if line.startswith(“def “) or line.startswith(“class … Read more

Most of the AI ​​memory remembers the user. It stores your preferences, interests, and roles. Confusion takes a different approach. Today, Perplexity was launched The brainself-improving memory system for its agent product, A computer. The brain does not focus on remembering. It remembers what the agent did. That redefines what memory in AI is. What … Read more

Many people use ChatGPT as a smart search engine. Ask a question, get an answer, and move on. It works but leaves a an incredible amount of value on the table. Over the past few years, ChatGPT has evolved beyond a simple chatbot. It can browse the web, analyze files, generate images, store memory, and … Read more

Large-scale linguistic models (LLMs) face a memory problem unrelated to model weights. During decoding, transformers store key and value (KV) vectors for all tokens in all layers so that they cannot be re-identified. This cache grows linearly with the length of the sequence and the size of the cluster, and in the long case where … Read more

Most biological benchmarks ask small, fact-based questions with clean answers. Scientists weigh incomplete evidence and make decisions. OpenAI released LifeSciBench and directly addresses that gap. Even the most powerful model goes through about one third of the work. The benchmark is far from perfect. What is LifeSciBench LifeSciBench contains 750 jobs written by experts. They … Read more