Made this using mickmumpitz’s ComfyUI workflow that lets you animate movement by manually shifting objects or images in the scene. I tested both my higher quality camera and my iPhone, and for this demo I chose the lower quality footage with imperfect lighting. That roughness made it feel more grounded, almost like the movement was …
As organizations scale their generative AI implementations, the critical challenge of balancing quality, cost, and latency becomes increasingly complex. With inference costs dominating 70–90% of large language model (LLM) operational expenses, and verbose prompting strategies inflating token volume by 3–5x, organizations are actively seeking more efficient approaches to model interaction. Traditional prompting methods, while effective, …
Read more “Move Beyond Chain-of-Thought with Chain-of-Draft on Amazon Bedrock”
Novo Nordisk’s semaglutide will soon be available in a daily pill Americans can take for weight loss.
“Feral” gossip spread via AI bots is likely to become more frequent and pervasive, causing reputational damage and shame, humiliation, anxiety, and distress, researchers have warned.
An analysis of the expansion of cracks in the Thwaites Glacier over the past 20 years suggests that a total collapse could be only a matter of time.
A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how systems evolve over time and reduces thousands of variables into compact equations that still capture real behavior. The method works across physics, engineering, climate science, and biology. Researchers say it could help scientists understand systems where …
Read more “This AI finds simple rules where humans see only chaos”
A new approach is making it easier to visualize lifelike 3D environments from everyday photos already shared online, opening new possibilities in industries such as gaming, virtual tourism and cultural preservation.
If you spend any time working with real-world data, you quickly realize that not everything comes in neat, clean numbers.
This article is divided into three parts; they are: • Training a Tokenizer with Special Tokens • Preparing the Training Data • Running the Pretraining The model architecture you will use is the same as the one created in the
This article is divided into two parts; they are: • Simple RoPE • RoPE for Long Context Length Compared to the sinusoidal position embeddings in the original Transformer paper, RoPE mutates the input tensor using a rotation matrix: $$ begin{aligned} X_{n,i} &= X_{n,i} cos(ntheta_i) – X_{n,frac{d}{2}+i} sin(ntheta_i) \ X_{n,frac{d}{2}+i} &= X_{n,i} sin(ntheta_i) + X_{n,frac{d}{2}+i} cos(ntheta_i) …
Read more “Rotary Position Embeddings for Long Context Length”