Dataiku

MARCH 25, 2024

This scenario is not science fiction but a glimpse into the capabilities of Multimodal Large Language Models (M-LLMs), where the convergence of various modalities extends the landscape of AI. But instead, a machine seamlessly identifies the scene and its location, provides a detailed description, and even suggests nearby attractions.

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Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities. So, if you have 1 trillion data points (g.,

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

IBM Big Data Hub

FEBRUARY 13, 2024

For example, organizations can use generative AI to: Quickly turn mountains of unstructured text into specific and usable document summaries, paving the way for more informed decision-making. This data is fed into generational models, and there are a few to choose from, each developed to excel at a specific task.

Enterprise 127

Enterprise Modeling Testing Data-driven 127

O'Reilly on Data

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Researchers are finding more and more ways to extract training data from ChatGPT and other models. And the space is moving quickly: SORA , OpenAI’s text-to-video model, is yet to be released and has already taken the world by storm.

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Modeling Machine Learning Risk Advertising 275

CIO Business Intelligence

MARCH 11, 2024

It will improve project management, help with requirements creation, assist developers with coding, cover the system with auto-tests, report defects, and improve deployment. It turns out, one tiny legacy component that was barely documented didn’t sustain the production volumes and brought down the whole system.

Software 98

Software Testing Data-driven Risk 98

IBM Big Data Hub

NOVEMBER 24, 2023

Subsequent phases are build and test and deploy to production. Modernization teams perform their code analysis and go through several documents (mostly dated); this is where their reliance on code analysis tools becomes important. Let us explore the Generative AI possibilities across these lifecycle areas.

Cost-Benefit 100

Cost-Benefit Testing Data-driven Enterprise 100

CIO Business Intelligence

MARCH 12, 2024

Early use cases include code generation and documentation, test case generation and test automation, as well as code optimization and refactoring, among others. Gen AI is also reducing the time needed to complete testing, via automation, Ramakrishnan says. One example is with document search and summarization.

Software 131

Software Experimentation Testing Cost-Benefit 131

AWS Big Data

NOVEMBER 17, 2023

It also applies general software engineering principles like integrating with git repositories, setting up DRYer code, adding functional test cases, and including external libraries. For more information, refer SQL models. When you run dbt test , dbt will tell you if each test in your project passes or fails.

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Snapshot Data Processing Testing Data Warehouse 87

CIO Business Intelligence

JUNE 6, 2022

As organisations pivot to hybrid working models, cloud collaboration tools have proved they are scalable, secure, and resilient – finally dispelling any lingering concerns that the technology is not yet enterprise ready. Russell makes the point that they must now resist the urge to revert to tried-and-tested pre-pandemic working models.

Modeling 98

Modeling Data-driven Testing Technology 98

erwin

JULY 11, 2019

At a fundamental level, digital transformation is about further synthesizing an organization’s operations and technology, so involving business architecture and process modeling is a best practice organizations cannot ignore. Business Process Modeling: The First Step to Giving Customers What They Expect. Data usage.

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Digital Transformation Modeling Data Governance Visualization 106

Cloudera

OCTOBER 18, 2023

In fact, some of the insights presented in this blog have been assisted by the power of large language models (LLMs), highlighting the synergy between human expertise and AI-driven insights. Testing: Generative AI can be used to generate test cases automatically, reducing the time and effort required for developers to test their code.

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Cost-Benefit Testing Machine Learning Optimization 75

CIO Business Intelligence

APRIL 2, 2024

Reducing productivity dips and easing end-user adoption then are practices that must fit the digital and transformation operating model. Documentation and well-written user stories guide teams in completing the work and meeting requirements. Leverage canary releases and control rolling out new capabilities to small user segments.

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Management Digital Transformation Testing Experimentation 140

erwin

SEPTEMBER 12, 2019

Strong internal business process modeling and management helps data-driven organizations compete and lead. In short, an internal business process is a documented account of how things should be done to maximize efficiency and achieve a particular goal. The Value of Internal Business Process Modeling.

Modeling 101

Modeling Cost-Benefit Data-driven Data Governance 101

O'Reilly on Data

JULY 11, 2023

He’s asking whether large language models eliminate programming as we know it, and he’s excited that the answer is “yes”: eventually, if not in the immediate future. Testing and debugging—well, if you’ve played with ChatGPT much, you know that testing and debugging won’t disappear. But what does this mean in practice?

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Testing Software Visualization Interactive 248

O'Reilly on Data

FEBRUARY 15, 2022

But a recent discussion of Google’s new Large Language Models (LLMs), and its claim that one of these models (named Gopher) has demonstrated reading comprehension approaching human performance , has spurred some thoughts about comprehension, ambiguity, intelligence, and will. Jack walked up the hill. Is this transgression?

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CIO Business Intelligence

MARCH 3, 2024

Worse, it said “adversaries are accelerating and widening their range of sophisticated attacks at scale through automation, cybercrime-as-a-service models, impersonations and adaptation.” Doing penetration testing. The administrator can also restrict duplication of documents containing keywords.

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IT Measurement Risk Testing 111

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

O'Reilly on Data

MAY 18, 2020

This article answers these questions, based on our combined experience as both a lawyer and a data scientist responding to cybersecurity incidents, crafting legal frameworks to manage the risks of AI, and building sophisticated interpretable models to mitigate risk. All predictive models are wrong at times?—just

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CIO Business Intelligence

DECEMBER 19, 2023

Be proactive and serve with empathy It cannot be stressed enough how important it is to be active in ensuring that all services delivered to end users are fully vetted and tested to the point where there’s no room for complaints. Have a service delivery model that’s predictable and consistent.”

IT 139

IT Testing Metrics Optimization 139

Smart Data Collective

AUGUST 22, 2021

The process involves confirmation and documentation that the computer software can consistently and accurately produce results that preset guidelines for quality management and compliance purposes. In doing so, they help ensure their research results, tests , and clinical records are accurate, repeatable, and verifiable.

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Data-driven Software Manufacturing Big Data 130

Ontotext

JUNE 27, 2019

It provides the core infrastructure for solutions where modeling agility, data integration, relationship exploration, cross-enterprise data publishing and consumption are critical. GraphDB: MongoDB Document Store Integration for Large-scale Metadata Management. Step 1: Importing our JSON LD document in GraphDB.

Metadata 40

Metadata Management Enterprise Optimization 40

O'Reilly on Data

MAY 25, 2021

GPT-3 is essentially an auto-complete bot whose underlying Machine Learning (ML) model has been trained on vast quantities of text available on the Internet. I’d like to share my thoughts on GPT-3 in terms of risks and countermeasures, and discuss real examples of how I have interacted with the model to support my learning journey.

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AWS Big Data

JANUARY 9, 2024

Lexical search In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word. Traditional lexical search, based on term frequency models like BM25, is widely used and effective for many search applications. Only items that have words the user typed match the query.

Cost-Benefit 88

Cost-Benefit Visualization Modeling Machine Learning 88

IBM Big Data Hub

JANUARY 8, 2024

The judiciary, like the legal system in general, is considered one of the largest “text processing industries” Language, documents, and texts are the raw material of legal and judicial work. As such, the judiciary has long been a field ripe for the use of technologies like automation to support the processing of documents.

Management 91

Management IT Digital Transformation Metadata 91

CIO Business Intelligence

SEPTEMBER 29, 2023

These skills include expertise in areas such as text preprocessing, tokenization, topic modeling, stop word removal, text classification, keyword extraction, speech tagging, sentiment analysis, text generation, emotion analysis, language modeling, and much more.

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Deep Learning Machine Learning Modeling Consulting 143

IBM Big Data Hub

APRIL 9, 2024

” The historical sources watsonx.data accesses comprise relational, object and document databases, including IBM® Db2® , IBM® Cloudant , IBM Cloud® Object Storage and PostgreSQL. “For the Masters we use 290 traditional AI models to project where golf balls will land,” says Baughman.

Management 88

Management IT Machine Learning Metrics 88

Ontotext

JUNE 27, 2019

One of the latest new features of GraphDB is the MongoDB document store integration. This is a really exciting feature as it increases the write scalability of RDF solutions when dealing with document-centric data. Its indices are designed for fast storage and retrieval of documents and objects. Fining documents.

Metadata 40

Metadata Management Optimization Enterprise 40

Ontotext

MARCH 15, 2024

Probably most of you have tried, but how many were able to figure out all the details of the described information – symptoms, laboratory tests, accompanying diseases, therapy, etc. The specifics of training such models do not require data in all the languages that you might target but rather a set of diverse examples.

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Modeling Metadata Testing Optimization 59

O'Reilly on Data

OCTOBER 10, 2023

ChatGPT responded with some fairly basic advice about following common Ruby naming conventions and avoiding inline comments (Rubyists used to think that code should be self-documenting. A rigorous test suite would have helped.) Testing has always been important (and under-utilized); with ChatGPT, it’s even more so.

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CIO Business Intelligence

DECEMBER 19, 2023

Many technology investments are merely transitionary, taking something done today and upgrading it to a better capability without necessarily transforming the business or operating model. These workstreams require documenting a vision, assigning leaders, and empowering teams to experiment.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

CIO Business Intelligence

DECEMBER 11, 2023

We promote innovation through regulatory sandboxes, real-world testing and open sources [excluding open source AI systems from transparency requirement]. Restrictions on GPAIS The growing popularity and adoption of GPAIS, such as ChatGPT, has pushed the authorities to accelerate the introduction of the governance model.

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CIO Business Intelligence

JANUARY 9, 2024

transition Step 1: Locate, identify and document all the credit card flow in the organization, as stated by the following requirements applicable to all entities subject to PCI security compliance: 1.2.4 See the PCI Security Standards Council (SSC) Requirements and Testing Procedures , Version 4.0 compliance steps. March 2022.)

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AWS Big Data

AUGUST 21, 2023

Lexical search looks for words in the documents that appear in the queries. For the demo, we’re using the Amazon Titan foundation model hosted on Amazon Bedrock for embeddings, with no fine tuning. In lexical search, the search engine compares the words in the search query to the words in the documents, matching word for word.

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Data Processing Experimentation Visualization Metrics 89

O'Reilly on Data

JULY 28, 2020

Product Managers are responsible for the successful development, testing, release, and adoption of a product, and for leading the team that implements those milestones. You must detect when the model has become stale, and retrain it as necessary. The Core Responsibilities of the AI Product Manager. The AI Product Development Process.

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Marketing Experimentation Metrics Testing 362

CIO Business Intelligence

SEPTEMBER 7, 2023

Additionally, it’s paramount within the financial services sector to ensure responsible AI and adherence to regulatory guidance for model risk. Managing GenAI testing and access with trusted partners We don’t have the luxury of waiting to see how AI evolves before it affects our everyday life.

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Risk Management Risk Testing Digital Transformation 98

CIO Business Intelligence

APRIL 1, 2024

“One of the biggest uses for gen AI is solving for the millions of lines of code that we still use and that doesn’t have any documentation.” But gen AI and large language models (LLMs) can get around these challenges, which drag down the velocity of many modernization projects.

Strategy 140

Strategy IT Digital Transformation ROI 140

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. According to Gartner, the goal is to design, model, align, execute, monitor, and tune decision models and processes. Model-driven DSS. They emphasize access to and manipulation of a model.

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