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Meituan Wang Xing Explains AI Strategy: No Code Platform Free to Use, 1680 Applications Launched

At the recent annual general meeting held at Meituan headquarters in Hengdian Building in Beijing, founder Wang Xing made a systematic exposition of the company's strategic layout and development plan in the field of artificial intelligence for the first time, revealing the deep thinking and bold practice of Meituan in the AI wave. Wang Xing divided Meituan's AI development into different stages. In the early stage, the company had already applied deep neural network algorithms in its food delivery route and dispatch systems. The current phase focuses on the development and deployment of large language models and their derivative applications. Facing fierce competition in the AI field, Meituan has carried out...

7.5k 3 days ago

Meituan Wang Xing Explains AI Strategy: No Code Platform Free to Use, 1680 Applications Launched

Huginn: A Novel Language Model Breaking Reasoning Limits, Enabling 'Thinking' Without Explicit Language

Researchers from the Tübingen University's ELLIS Unit, the University of Maryland, and Lawrence Livermore National Laboratory have developed Huginn, a novel language model with a recursive architecture that significantly enhances reasoning capabilities. Unlike traditional models, Huginn doesn't require specialized 'reasoning chain' training; it can autonomously reason within the neural network's 'latent space' before outputting results. The research team developed Huginn, a novel language model with a recursive architecture that significantly enhances reasoning abilities. Unlike...

12.9k 10 hours ago

Huginn: A Novel Language Model Breaking Reasoning Limits, Enabling 'Thinking' Without Explicit Language

AI Has Fatal Flaws in This Area! Experts: AI Should Not Be Used in Critical Applications

In the current technological environment, artificial intelligence (AI) has sparked widespread discussion. Eerke Boiten, a professor of cybersecurity at De Montfort University, states that existing AI systems have fundamental flaws in management and reliability, and therefore should not be used in critical applications. Professor Boiten points out that most current AI systems rely heavily on large neural networks, particularly generative AI and large language models (like ChatGPT). The workings of these systems are relatively complex, even though each neural...

14.7k 2 hours ago

AI Has Fatal Flaws in This Area! Experts: AI Should Not Be Used in Critical Applications

Meta Releases New Memory Layer Technology: Breaking Parameter Limits and Significantly Improving AI Fact Accuracy

Recently, Meta has announced a groundbreaking research achievement by developing a new type of memory layer technology that can significantly enhance the factual accuracy of large language models (LLMs) and achieve unprecedented expansion in parameter scale. This technology not only challenges traditional neural network expansion methods but also provides new directions for future AI architecture design. The core of this research lies in utilizing a trainable key-value lookup mechanism to add extra parameters to the model without increasing computational load (FLOPs). This method's core thinking is...

27.2k 10-29

Models

Pacific Prime

Pacific-Prime

The INL architecture is a production-level neural architecture based on integral neuron dynamics, replacing traditional feed-forward network layers with iterative dynamics. It is suitable for various types of models such as large language models, vision transformers, and multi-modal models.

Natural Language Processing

SafetensorsEnglish

Pacific-Prime

147

Control_v11p_sd15_inpaint

krnl

ControlNet v1.1 is a neural network architecture based on diffusion models, designed to control image generation through additional conditions, particularly suited for image inpainting tasks.

Computer Vision

DiffusersOther

krnl

Control_v11p_sd15_lineart

shuai1106

ControlNet v1.1 is a neural network architecture based on line art image conditions, designed to control pre-trained diffusion models to support additional input conditions.

Computer Vision

DiffusersOther

shuai1106

Controlnet Inpaint Endpoint

OrderAndChaos

ControlNet v1.1 is a neural network architecture based on Stable Diffusion, designed to control diffusion models through image inpainting conditions.

Computer Vision

DiffusersOther

OrderAndChaos

Control_v11f1e_sd15_tile

lllyasviel

ControlNet v1.1 is a neural network structure that controls pre-trained large diffusion models by adding additional conditions. It is particularly suitable for image generation and super-resolution tasks based on tile image conditions.

Control_v11f1e_sd15_tile

ControlNet-1-1-preview

ControlNet v1.1 is a neural network architecture based on diffusion models, designed to control pre-trained large diffusion models by adding additional conditions.

Computer Vision

DiffusersOther

ControlNet-1-1-preview

Control_v11e_sd15_ip2p

lllyasviel

ControlNet v1.1 is a neural network structure developed by Lvmin Zhang, designed to control large pre-trained diffusion models through additional conditions. This version is trained based on instruct pix2pix image conditions.

Sd Controlnet Scribble

lllyasviel

ControlNet is a neural network structure that controls diffusion models through doodle image conditions, enabling precise generation of images matching sketch outlines.

Sd Controlnet Mlsd

lllyasviel

ControlNet is a neural network structure that controls diffusion models by adding additional conditions. This checkpoint corresponds to the ControlNet model trained with M-LSD straight-line detection conditions.

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