insideBIGDATA

OCTOBER 14, 2023

A recent survey of data scientists and engineers revealed that over half (53.3%) of today’s machine learning (ML) teams are planning on deploying a large language model (LLM) application of their own into production “within the next 12 months” or “as soon as possible”. Perhaps even more startling, however, is the finding that nearly one in ten (8.3%) enterprise ML teams have already deployed an LLM application into production.

Data Scientist 307

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Eugene Yan

OCTOBER 14, 2023

The biggest deployment challenges, backward compatibility, multi-modality, and SF work ethic.

AI 314

AI AI 314

insideBIGDATA

OCTOBER 14, 2023

In this contributed article, Ashley Leonard, president and CEO of Syxsense, reflects on some of the most pertinent issues affecting the adoption of generative AI in security. These include the question of who owns the AI output, how to conduct quality assurance to mitigate unwanted results, and companies' overall preparedness to manage workforce displacement.

AI 243

AI AI Big Data Big Data 243

Eugene Yan

OCTOBER 14, 2023

The biggest deployment challenges, backward compatibility, multi-modality, and SF work ethic.

AI 144

AI AI 144

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Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Data Science 101

OCTOBER 14, 2023

Threads Dev Interviews I am finding developers on Threads and interviewing them, right on Threads. You are welcome to follow along and let me know on Threads if you would like to be interviewed. Note: The views in these interviews are personal views and do not represent the interviewee’s employer. “We saw researchers, students and developers unlock amazing use cases with VR once devices became easily accessible and affordable, so I want to see that happen with MR and AR glasses as so

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Hacker News

OCTOBER 14, 2023

Introduction to USB.

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Mlearning.ai

OCTOBER 14, 2023

Introduction Deep learning tasks usually demand high computation/memory requirements and their computations are embarrassingly parallel. In this way, high-performance computing (HPC) systems are a good target for them. The paper claims that distributed training has been facilitated by deep learning frameworks, but fault tolerance did not get enough attention.

Deep Learning 52

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Mlearning.ai

OCTOBER 14, 2023

`pip install hypertab` is all you need Overview of the article: Why are tabular data so interesting? Introduction to hypernetworks What is HyperTab? Why use HyperTab? How to use HyperTab? How does HyperTab perform? GitHub - wwydmanski/hypertab Why are tabular data so interesting? Different types of datasets. Source: [parrot] , [time series] There are many different types of data —real world images, time series, natural language, and, of course, tabular.

Deep Learning 52

Deep Learning Deep Learning Data Analysis Data Analysis 52