What is coding skew and how to fix it?
words = [p[1] for p in pairs] ids_ws = [tokenizer.encode(” ” + w, add_special_tokens=False)[0] for w in words] ids_nws =…
Category: Ai and Innovation
latest development in field of AI
Sakana AI offers KAME: a tandem speech-to-speech architecture that injects LLM knowledge in real-time
The fundamental tension in conversational AI has always been a binary choice: rapid response or intelligent response. Real-time speech-to-speech (S2S)…
Mistral AI launches remote agents in Vibe and Mistral Medium 3.5 with 77.6% SWE-Bench verification score
Mistral AI is building one of the most practical coding agent ecosystems in the open source AI/weights space, and is…
Build a multi-agent AI workflow for biological network modeling, protein interactions, metabolism, and cell signaling simulation
class CellSignalingSimulationAgent: def run(self, df_signal: pd.DataFrame) -andgt; AgentResult: peak_receptor = float(df_signal[“receptor_active”].max()) peak_kinase = float(df_signal[“kinase_active”].max()) peak_tf = float(df_signal[“tf_active”].max()) t_receptor = float(df_signal.loc[df_signal[“receptor_active”].idxmax(),…
Implementing a coding implementation to parse, parse, visualize, and fine-tune agent reasoning traces using the lambda/hermes-agent-reasoning-traces dataset.
In this tutorial, we explore lambda/hermes-inference-dataset To understand how agent-based models think, use tools, and create responses across multi-turn conversations.…
New NVIDIA research shows that speculative decoding in NeMo RL achieves 1.8x generation speedup at 8B and expects 2.5x overall speedup at 235B
If you’ve been running reinforcement learning (RL) after training a language model for mathematical reasoning, code generation, or any verifiable…
Implementing an encoding for end-to-end brain decoding of MEG signals using NeuralSet and deep learning to predict linguistic features
EPOCHS = 15 opt = torch.optim.AdamW(model.parameters(), lr=1e-3, weight_decay=1e-4) sched = torch.optim.lr_scheduler.CosineAnnealingLR(opt, T_max=EPOCHS) loss_fn = nn.MSELoss() hist = {“tr”: [], “va”:…
Meta presents Automatic Data: a powerful framework that turns AI models into independent data scientists to create high-quality training data
The bottleneck in building better AI models has never been compute alone, it has always been data quality. Meta AI’s…
Microsoft Research’s World-R1 uses Flow-GRPO and 3D-Aware bonuses to inject geometric consistency into Wan 2.1 without architectural changes
Video based models can draw a beautiful frame. And they are still very bad at remembering it. Push the camera…
Qwen AI launches Qwen-Scope: an open source sparse autoencoder (SAE) toolkit that turns in-house LLM features into practical development tools
Large linguistic models are remarkably capable, but frustratingly vague. When a model misbehaves – such as generating responses in the…