Marktechpost

OCTOBER 28, 2024

Firstly, the constant online interaction and update cycle in RL places major engineering demands on large systems designed to work with static ML models needing only occasional offline updates. In this, the limitation learning algorithm combines trajectories to learn a new policy.

Machine Learning 114

Machine Learning Algorithm Inference Engine ML 114

Marktechpost

OCTOBER 19, 2024

The problem of over-optimization of likelihood in Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), arises when these methods fail to improve model performance despite increasing the likelihood of preferred outcomes. If you like our work, you will love our newsletter.

Inference Engine 107

Inference Engine Algorithm LLM ML 107

Marktechpost

AUGUST 2, 2024

ML algorithms learn from data to improve over time, while DL uses neural networks to handle large, complex datasets. These systems rely on a domain knowledge base and an inference engine to solve specialized medical problems. AI, particularly through ML and DL, has advanced medical applications by automating complex tasks.

Artificial Intelligence 120

Artificial Intelligence Artificial Intelligence Robotics Deep Learning 120

Marktechpost

AUGUST 5, 2024

Several search engines have attempted to improve the relevance of search results by integrating advanced algorithms and machine learning models. Additionally, many of these search engines are not open-source, limiting the ability for broader community involvement and innovation.

Inference Engine 111

Inference Engine Machine Learning AI AI 111

Unite.AI

JULY 18, 2024

This involves tweaking algorithms, fine-tuning models, and using tools and frameworks that support cross-platform compatibility. Language Processing Units (LPUs): The Language Processing Unit (LPU) is a custom inference engine developed by Groq, specifically optimized for large language models (LLMs).

Neural Network 157

Neural Network AI Modeling AI AI 157

Marktechpost

OCTOBER 26, 2024

Further, researchers presented WORFEVAL, a systematic evaluation protocol utilizing advanced subsequence and subgraph matching algorithms to evaluate chain and graph structure workflow generation. In conclusion, researchers introduced WORFBENCH, a method to evaluate workflow generation capabilities in LLM agents.

Large Language Models 111

Large Language Models LLM Inference Engine Algorithm 111

Marktechpost

OCTOBER 16, 2024

Evaluating the performance of quantum computers has been a challenging task due to their sensitivity to noise, the complexity of quantum algorithms, and the limited availability of powerful quantum hardware. Decoherence and errors introduced by noise can significantly affect the accuracy of quantum computations.

AI Research 120

AI Research AI Researcher Inference Engine Algorithm 120

Marktechpost

OCTOBER 19, 2024

These differences make it challenging to directly relate visual perception to action control, requiring intermediate representations or learning algorithms to bridge the gap. Currently, robots are represented by geometric primitives like triangle meshes, and kinematic structures describe their morphology.

Robotics 110

Robotics Inference Engine Algorithm ML 110

Marktechpost

OCTOBER 16, 2024

Online RL algorithms iteratively take actions, collecting observations and rewards from the environment, and then update their policy using the latest experience. a) It contains a diversity of tasks including tasks where state-of-the-art algorithms struggle to drive the development of novel algorithms. (b)

Inference Engine 107

Inference Engine Algorithm ML AI 107

Marktechpost

OCTOBER 17, 2024

However, adversarial attacks on AI algorithms can manipulate energy flows, disrupting the balance between vehicles and the grid and potentially compromising user privacy by exposing sensitive data like vehicle usage patterns. However, using Conditional GAN for data augmentation significantly reduces DBSCAN’s effectiveness.

Machine Learning 106

Machine Learning Inference Engine Categorization AI 106

Marktechpost

OCTOBER 21, 2024

While explicit search methods like Monte Carlo Tree Search (MCTS) have been employed to enhance decision-making in various AI systems, including chess engines and game-playing algorithms, they present challenges when applied to LLMs. If you like our work, you will love our newsletter. Don’t Forget to join our 50k+ ML SubReddit.

Neural Network 102

Neural Network Inference Engine Large Language Models Algorithm 102

Marktechpost

OCTOBER 16, 2024

Optimization-based attacks use automatic algorithms to generate jailbreak prompts based on feedback, such as loss function gradients or by training generators to imitate optimization algorithms. Existing jailbreak attempts primarily follow two methodological approaches: optimization-based and strategy-based attacks.

Large Language Models 111

Large Language Models Inference Engine LLM Algorithm 111

Marktechpost

OCTOBER 25, 2024

Thus, one can conduct training for such a strategy on complex tasks like maze navigation or Sokoban games using traces generated by the A* search algorithm​. The model constructed is based on a systematic trace-dropping method where the traces of reasoning are progressively pruned over the training process to instill efficiency.

Auto-complete 110

Auto-complete Inference Engine AI AI 110

Marktechpost

OCTOBER 15, 2024

By eliminating the need for calibration data and relying on deterministic offline algorithms, SeedLM simplifies the compression process while retaining high accuracy levels. The FPGA implementation further emphasizes its potential in real-world applications, providing up to a 4x speed-up in memory-bound tasks.

LLM 107

LLM Natural Language Processing Inference Engine Large Language Models 107

Towards AI

AUGUST 29, 2023

Frequently, Python code invokes C++ methods for intricate algorithmic calculations. However, I encountered an opposite scenario where my Machine Learning application urgently required invoking a custom model with Python-based inference code. My initial thought was simple: “Calling Python from C++ should be a breeze.”

Python 98

Python Inference Engine Machine Learning Algorithm 98

Marktechpost

OCTOBER 26, 2024

These approaches typically involve training reward models on human preference data and using algorithms like Proximal Policy Optimization (PPO) or Direct Policy Optimization (DPO) for policy learning. If you like our work, you will love our newsletter. Don’t Forget to join our 55k+ ML SubReddit.

AI Research 105

AI Research AI Researcher Data Scarcity Inference Engine 105

Marktechpost

OCTOBER 18, 2024

Similarly, HumanEval and MBPP evaluate code generation only in basic, algorithmic tasks, failing to reflect the complexity of real-world AI development. Benchmarks like SWE-Bench, for example, focus on the success rate of final solutions in long-term automated tasks but offer little insight into the performance of intermediate steps.

Large Language Models 107

Large Language Models LLM AI Development AI Developer 107

Marktechpost

JUNE 8, 2023

The regular expression, LLM decision rules, and the traversal algorithm are all stored in the Query Object. A regular expression inference engine that effectively converts regular expressions to finite automata has been designed and implemented. They are the first group to use automata to accommodate these variant encodings.

Large Language Models 107

Large Language Models LLM Inference Engine AI 107

Marktechpost

JUNE 19, 2023

FlashAttention, on the other hand, is a precise attention algorithm that considers hardware configurations to achieve better performance. Reformer uses a sparse approximation to reduce computing cost, while other works use low-rank or a combination of approximation techniques.

Inference Engine 97

Inference Engine ML AI Tools Deep Learning 97

Marktechpost

OCTOBER 17, 2024

Rigorous testing was done on a wide range of problems that involved algorithmic challenges to real-world applications. Further experiments conducted on various LLMs revealed 25% logic errors that were missed by the conventional unit tests. Multiple code generation models were used for assessing the robustness of the model.

Machine Learning 64

Machine Learning Software Development Inference Engine Large Language Models 64

AWS Machine Learning Blog

APRIL 3, 2023

The causal inference engine is deployed with Amazon SageMaker Asynchronous Inference. SageMaker Asynchronous Inference allows queuing incoming requests and processes them asynchronously. In this post, we demonstrate how to create this counterfactual analysis using Amazon SageMaker JumpStart solutions.

Inference Engine 93

Inference Engine Machine Learning Algorithm Data Scientist 93

Marktechpost

OCTOBER 21, 2024

These include techniques like ablation studies, where specific model components are disabled to observe their role, and clustering algorithms, which group similar components based on their behavior. Several tools have been developed to study how neural networks operate. If you like our work, you will love our newsletter.

Machine Learning 60

Machine Learning Neural Network Natural Language Processing Inference Engine 60

Mlearning.ai

JUNE 2, 2023

In order to tackle this, the team at Modular developed a modular inference engine. Designed by Canva Have you guys ever heard of Modular? This highly complex and fragmented ecosystem is hampering the AI innovation, and is pulling back the AI community, as a whole. Read more about it here.

Inference Engine 52

Inference Engine Python Machine Learning Neural Network 52

Marktechpost

OCTOBER 23, 2024

In coding tasks, the o1 model was evaluated using the USACO dataset, a benchmark that tests the model’s algorithmic and problem-solving skills. This approach contrasted with models like GPT-4o, which relied more heavily on scaling parameters but needed help with multi-step reasoning tasks that required a more structured approach.

Inference Engine 56

Inference Engine Large Language Models LLM OpenAI 56

Mlearning.ai

JANUARY 28, 2023

TensorFlow: TensorFlow is an open source library for building neural networks and other deep learning algorithms on top of GPUs. It offers various data type conversions and aggregations as well as powerful plotting capabilities.

Data Science 52

Data Science Machine Learning ML Python 52

Mlearning.ai

MAY 16, 2023

. * @return the predicted class */ std::string Inference(cv::Mat& src, AAssetManager* mgr); #endif //IMAGECLASSIFICATION_INFERENCE_H /** * inference.cpp */ #include <algorithm> #include <vector> #include <string> #include <opencv2/imgproc.hpp> #include "net.h" f, 0.4822f*255.f,

Neural Network 98

Neural Network Convolutional Neural Networks Deep Learning Inference Engine 98

ODSC - Open Data Science

MARCH 8, 2024

gemma.cpp is a lightweight, standalone C++ inference engine for the Gemma foundation models from Google. Massachusetts-based Overjet , an AI-powered dental technology company that provides algorithms to analyze dental images and deliver diagnoses raised over $130M from private investors. raised $600M from private investors.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Science Large Language Models 52

AWS Machine Learning Blog

MAY 8, 2023

With kernel auto-tuning, the engine selects the best algorithm for the target GPU, maximizing hardware utilization. Overall, TensorRT’s combination of techniques results in faster inference and lower latency compared to other inference engines.

ML 94

ML BERT Deep Learning Auto-complete 94

Towards AI

JULY 19, 2023

Once the model is trained we test the model on sample images or videos Inference Running inference using Monk is even simpler ★ Step-1 — Import and initiate the Inference Engine ★ Step-2 — Load the trained Model ★ Step-3— Run inference on image The final output can be displayed in the jupyter notebook in this manner!!

Robotics 40

Robotics Computer Vision Deep Learning Inference Engine 40

AWS Machine Learning Blog

APRIL 20, 2023

With advancements in hardware design, a wide range of CPU- and GPU-based infrastructures are available to help you speed up inference performance. Because XGBoost is a memory-intensive algorithm, we provide ml.m5 type instances to get instance type recommendations. large", "ml.m5.xlarge",

ML 90

ML Auto-classification Python Auto-complete 90

Bugra Akyildiz

SEPTEMBER 8, 2024

The team had to carefully tune their algorithms and leverage hierarchical communication patterns to maintain efficiency. Numerical stability: At such large scales, ensuring numerical stability of the training process became more challenging, potentially requiring adjustments to the optimization algorithm or learning rate schedules.

LLM 52

LLM Large Language Models Neural Network Machine Learning 52

Google Research AI blog

JUNE 15, 2023

As discussed in our previous blog post , GPU-accelerated ML inference is often limited by memory performance, and execution of LDMs is no exception. Ultimately, our primary objective is to reduce the overall latency of the ML inference.

Inference Engine 92

Inference Engine ML Algorithm Software Engineer 92

Marktechpost

OCTOBER 23, 2024

Moreover, the integration of a novel sampling algorithm called Tournament sampling within SynthID-Text has enhanced detection performance by embedding statistical signatures that are challenging to remove. The results are promising: during testing, SynthID identified watermarked text with an accuracy rate exceeding 95%.

Large Language Models 107

Large Language Models Responsible AI Inference Engine Metadata 107

Towards AI

JULY 19, 2023

github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. DeepSparse: a CPU inference engine for sparse models. Follow their code on GitHub. SparseZoo: a model repo for sparse models.

NLP 98

NLP Neural Network Natural Language Processing BERT 98

Towards AI

JULY 21, 2023

github.com Their core repos consist of SparseML: a toolkit that includes APIs, CLIs, scripts and libraries that apply optimization algorithms such as pruning and quantization to any neural network. DeepSparse: a CPU inference engine for sparse models. Follow their code on GitHub. SparseZoo: a model repo for sparse models.

NLP 52

NLP Neural Network Natural Language Processing BERT 52

Marktechpost

OCTOBER 28, 2024

Invariant learning approaches enhance robustness to distributional changes by enforcing that models remain consistent across environments; however, in cases without predefined environments, data subsets can be created to challenge invariant constraints, using algorithms like groupDRO to improve distributional robustness.

Neural Network 110

Neural Network Inference Engine Machine Learning Automation 110

AI Impacts

OCTOBER 28, 2024

In addition, I link philosophical reasoning to conceptual/qualitative/non-paradigmatic research, arguing that they’re implemented using the same cognitive algorithms. One of these steps consists of relating empirical evidence to theoretical and decision-relevant propositions.

Automation 162

Automation Explainability AI AI 162