IBM Journey to AI blog

NOVEMBER 24, 2023

The inability to visualize the API portfolio from a Banking Industry Model perspective constrains the Business and IT teams to understand the capabilities that are already available and what new capabilities are needed for the bank. It also requires some focused effort to improve the data quality of data needed for tuning the models.

Generative AI 248

Generative AI Auto-complete DevOps Automation 248

Heartbeat

MAY 29, 2023

LLMs are one of the most exciting advancements in natural language processing (NLP). This technique is commonly used in neural network-based models such as BERT, where it helps to handle out-of-vocabulary words. There are several pre-trained LLMs available that can be used for transfer learning, such as GPT-2, BERT, and RoBERTa.

Large Language Models 78

Large Language Models LLM Machine Learning Natural Language Processing 78

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Natural language processing to extract key information quickly. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data.

Large Language Models 52

Large Language Models AI AI Natural Language Processing 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Natural language processing to extract key information quickly. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data.

Large Language Models 52

Large Language Models AI AI Natural Language Processing 52

Snorkel AI

AUGUST 24, 2023

Machine learning to identify emerging patterns in complaint data and solve widespread issues faster. Natural language processing to extract key information quickly. Data quality is essential for the success of any AI project but banks are often limited in their ability to find or label sufficient data.

Large Language Models 52

Large Language Models AI AI Natural Language Processing 52

Heartbeat

OCTOBER 12, 2023

Large language models have been game-changers in artificial intelligence, but the world is much more than just text. These language models are breaking boundaries, venturing into a new era of AI — Multi-Modal Learning. However, the influence of large language models extends beyond text alone.

Large Language Models 59

Large Language Models Neural Network Artificial Intelligence Artificial Intelligence 59

Snorkel AI

OCTOBER 4, 2023

FMs can even transform dense tabular data into digestible consumer profiles. Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers.

AI 64

AI AI Data Scientist Neural Network 64

Snorkel AI

OCTOBER 4, 2023

FMs can even transform dense tabular data into digestible consumer profiles. Data scientists can train large language models (LLMs) and generative AI like GPT-3.5 to generate natural language reports from tabular data that help human agents easily interpret complex data profiles on potential borrowers.

AI 59

AI AI Data Scientist Neural Network 59

Marktechpost

NOVEMBER 10, 2023

Recent NLP research has focused on improving few-shot learning (FSL) methods in response to data insufficiency challenges. While these methods enhance model capabilities through architectural designs and pre-trained language models, data quality and quantity limitations persist.

BERT 124

BERT ChatGPT Large Language Models NLP 124

Bugra Akyildiz

FEBRUARY 5, 2023

Given the growing use of language models in NLP research and applications, it is important to better understand abilities such as these that can arise unexpectedly. Libraries Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not.

Large Language Models 52

Large Language Models Neural Network Machine Learning BERT 52

Sebastian Ruder

JANUARY 24, 2022

In speech, new models have been built based on wav2vec 2.0 [6] 6] such as W2v-BERT [7] as well as more powerful multilingual models such as XLS-R [8]. At the same time, we saw new unified pre-trained models for previously under-researched modality pairs such as for videos and language [9] as well as speech and language [10].

NLP 52

NLP ML BERT Computational Linguistics 52

AWS Machine Learning Blog

APRIL 17, 2023

Quantization and compression can reduce model size and serving cost by reducing the precision of weights or reducing the number of parameters via pruning or distillation. Compilation can optimize the computation graph and fuse operators to reduce memory and compute requirements of a model.

Prompt Engineer 78

Prompt Engineer Prompt Engineering Deep Learning Large Language Models 78

Topbots

JUNE 6, 2023

Autoencoding models, which are better suited for information extraction, distillation and other analytical tasks, are resting in the background — but let’s not forget that the initial LLM breakthrough in 2018 happened with BERT, an autoencoding model. Scaling Laws for Neural Language Models. [7] 7] Jason Wei et al.

LLM 105

LLM ChatGPT Prompt Engineer Prompt Engineering 105