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Same AI + Different Deployment Plans = Different Ethics
24 May

Same AI + Different Deployment Plans = Different Ethics

stp2y0 CommentsViral News
This month I will address an aspect of the ethics of artificial intelligence (AI) and analytics that I think many people don't fully appreciate. Namely, the ethics of a given algorithm can vary based on the specific scope and context of the deployment being proposed. What is considered unethical within one scope and context might be perfectly fine in another. I'll illustrate with an example and then provide steps you can take to make sure your AI deployments stay ethical. Why Autonomous Cars Aren't Yet Ethical For Wide Deployment There are limited tests of fully autonomous, driverless cars happening around…
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How Real-World Enterprises are Leveraging Generative AI
24 May

How Real-World Enterprises are Leveraging Generative AI

stp2y0 CommentsViral News
Generative AI (GenAI) is moving incredibly fast. So much so, that in less than two years, GenAI has emerged as one of the most exciting and transformative technologies, empowering enterprises across diverse industries to drive innovation, enhance productivity, and deliver exceptional customer experiences. At Databricks, we've seen exponential growth in the demand and development of GenAI applications across our platform from every sector of industry, be that communications, energy, financial services, healthcare and life sciences, manufacturing, public sector, media and entertainment, or retail and consumer goods.As we approach Data + AI Summit, we'll be bringing together a global community to…
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Text Generation using GPT2
24 May

Text Generation using GPT2

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The first ever GPT model was released by OpenAI in 2018. Since then, we have seen tremendous research and models based on the same architecture. Although GPT1 is old by today’s standards, GPT2 still holds fairly well for many fine-tuning tasks. In this article, we will dive into fine-tuning GPT2 for text generation. In particular, we will teach the model to generate detective stories based on Arthur Conan Doyle’s Sherlock Holmes series. Figure 1. Text generation example using the trained GPT2 model. GPTs and similar large language models can be fine-tuned for various text generation tasks. With this article, we…
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Can Scale Become the ‘Data Foundry’ for AI?
24 May

Can Scale Become the ‘Data Foundry’ for AI?

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(DedMityay/Shutterstock) Scale AI, which provides data labeling and annotation software and services to organizations like OpenAI, Meta, and the Department of Defense, this week announced a $1-billion funding round at a valuation of nearly $14 billion, putting it in a prime position to capitalize on the generative AI revolution. Alexandr Wang founded Scale AI back in 2016 to provide labeled and annotated data, primarily for autonomous driving systems. At the time, self-driving vehicles seemed to be just around the corner, but getting the vehicles on the road in a safe manner has proven to be a tougher problem than originally…
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Data Machina #250
23 May

Data Machina #250

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Llama 3: A Watershed AI moment? I reckon that the release of Llama 3 is perhaps one of the most important moments in AI development so far. The Llama 3 stable is already giving birth to all sorts of amazing animals and model derivatives. You can expect Llama 3 will unleash the mother of all battles against closed AI models like GPT-4.Meta AI just posted: ”Our largest Llama 3 models are over 400B parameters. And they are still being trained.” The upcoming Llama-400B will change the playing field for many independent researchers, little AI startups, one-man AI developers, and also…
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The Ethical Implications of AI in the Travel Industry
23 May

The Ethical Implications of AI in the Travel Industry

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Artificial Intelligence (AI) is transforming the travel industry by enhancing efficiency, personalization, and customer experience. However, as with any technological advancement, the adoption of AI brings a range of ethical implications that must be carefully considered. This article explores five key areas of ethical concern regarding AI in the travel industry. 1. Privacy and Data Security Data Collection and Usage: AI systems rely on vast amounts of personal data to function effectively, raising significant privacy concerns. The collection of data such as travel preferences, personal identification, and payment details necessitates stringent data protection measures. Risk of Data Breaches: The travel…
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Announcing simplified XML data ingestion
23 May

Announcing simplified XML data ingestion

stp2y0 CommentsViral News
We're excited to announce native support in Databricks for ingesting XML data.XML is a popular file format for representing complex data structures in different use cases for manufacturing, healthcare, law, travel, finance, and more. As these industries find new opportunities for analytics and AI, they increasingly need to leverage their troves of XML data. Databricks customers ingest this data into the Data Intelligence Platform, where other capabilities like Mosaic AI and Databricks SQL can then be used to drive business value.However, it can take a lot of work to build resilient XML pipelines. Since XML files are semi-structured and arbitrarily…
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Instruction Tuning OPT-125M
23 May

Instruction Tuning OPT-125M

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Large language models are pretrained on terabytes of language datasets. However, the pretraining dataset and strategy teach the model to generate the next token or word. In a real world sense, this is not much useful. Because in the end, we want to accomplish a task using the LLM, either through chat or instruction. We can do so through fine-tuning an LLM. Generally, we call this instruction tuning of the language model. To this end, in this article, we will use the OPT-125M model for instruction tuning. Figure 1. Output sample after instruction tuning OPT-125M on the Open Assistant Guanaco…
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Sigma Secures $200M Round to Advance Its BI and Analytics Solutions
23 May

Sigma Secures $200M Round to Advance Its BI and Analytics Solutions

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(NicoElNino/Shutterstock) Sigma Computing, a cloud-based analytics solutions provider, has raised $200 million in Series D funding to further advance its efforts in broadening BI use within organizations by enabling users to query and analyze data without writing code.  The latest rounding of funding takes the vendor’s total funding to $581.3 million with a valuation estimated to be around $1.5 billion, a staggering rise of 60% since the last funding round in 2021. The steep rise in valuation is partially a result of rising demand for greater productivity and monetization in the era of cloud data transition.  Spark Capital and Avenir…
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Data Machina #251
23 May

Data Machina #251

stp2y0 CommentsViral News
Three New Powerful Open AI Models. I’m told by colleagues at Hugging Face that just a week since LLama-3 was released, more than +10,000 model derivatives have been developed! The pressure on black-box, closed AI models is huge, and achieving GPT-4 performance with open, smallish models is upon us. Which is great. In the last few days, three new, smallish, powerful open AI models were released. Interestingly enough, the power of these 3 models is based on a combination of: 1) Innovative training architectures and optimisation techniques, and 2) Data quality for different types of data (synthetic, public or private).…
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