IBM Big Data Hub

SEPTEMBER 27, 2023

Large language models (LLMs) are foundation models that use artificial intelligence (AI), deep learning and massive data sets, including websites, articles and books, to generate text, translate between languages and write many types of content. All this reduces the risk of a data leak or unauthorized access.

Risk 91

Risk Modeling Cost-Benefit Enterprise 91

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. Related to this is the need to monitor bias, locality effects, and related risks.

Modeling 249

Modeling Machine Learning Testing Metrics 249

IBM Big Data Hub

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

Occam's Razor

MARCH 30, 2017

People tend to use these phrases almost interchangeably: Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. Deep Learning is a specific ML technique. Most Deep Learning methods involve artificial neural networks, modeling how our bran works. Here’s the higher-order-bit….

Marketing Analytics 166

Marketing Analytics Marketing Analytics Deep Learning 166

CIO Business Intelligence

FEBRUARY 10, 2023

With predictive analytics, organizations can find and exploit patterns contained within data in order to detect risks and opportunities. Such models enable the assessment of either the promise or risk presented by a particular set of conditions, guiding informed decision-making across various categories of supply chain and procurement events.

Predictive Analytics 145

Predictive Analytics Analytics Predictive Modeling Forecasting 145

CIO Business Intelligence

SEPTEMBER 19, 2023

Organizations all around the globe are implementing AI in a variety of ways to streamline processes, optimize costs, prevent human error, assist customers, manage IT systems, and alleviate repetitive tasks, among other uses. And with the rise of generative AI, artificial intelligence use cases in the enterprise will only expand.

Enterprise 141

Enterprise Cost-Benefit Optimization Deep Learning 141

Smart Data Collective

JUNE 4, 2021

In reinforcement learning the algorithm teaches itself how to complete a task. The list of rewards and risks is given as input to the algorithm. The algorithm deduces the best approaches to maximize rewards and minimize risks. Semi-Supervised Learning. Deep Learning. Reinforcement. Ensembling.

Data Science 133

Data Science Statistics Deep Learning Machine Learning 133

O'Reilly on Data

FEBRUARY 18, 2020

There’s plenty of security risks for business executives, sysadmins, DBAs, developers, etc., Normalized search frequency of top terms on the O’Reilly online learning platform in 2019 (left) and the rate of change for each term (right). to be wary of. Figure 1 (above).

Data-driven 363

Data-driven Software Statistics Marketing 363

CIO Business Intelligence

AUGUST 13, 2024

Unlike siloed or shallow automation efforts, deep automation architects a perspective that integrates customer experiences, value streams, human-machine collaboration, and synergistic technologies to create intelligent, self-adjusting businesses. It emphasizes end-to-end integration, intelligent design, and continuous learning.

Data-driven 130

Data-driven Metrics Optimization Deep Learning 130

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. A stock-out of an item may put a patient’s health at risk, but keeping huge amounts of inventory is very costly.

Statistics 84

Statistics Machine Learning Deep Learning Sales 84

O'Reilly on Data

MARCH 31, 2020

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. Managing Machine Learning Projects” (AWS).

Management 363

Management Machine Learning Experimentation Metrics 363

CIO Business Intelligence

JUNE 2, 2022

These technologies include deep learning , AI-powered robotic process automation , augmented reality , data mesh (a distributed architecture for data management), blockchain or distributed ledger technology, low-code platforms, progressive web apps , service mesh and event-driven architectures.

Predictive Analytics 145

Predictive Analytics Technology Analytics Machine Learning 145

The Unofficial Google Data Science Blog

NOVEMBER 17, 2020

The first is that they are straightforward to optimize using traditional gradient-based optimizers as long as we pre-specify the placement of the knots. There is a robust set of tools for working with these kinds of constrained optimization problems. PLFs have two useful properties that we take advantage of.

Machine Learning 111

Machine Learning Deep Learning Modeling Interactive 111

Domino Data Lab

MARCH 11, 2021

In this article, we’ll show key considerations for selecting the right machine learning framework for your project and briefly review four popular ML frameworks. Here are several key considerations you should take into account when selecting a machine learning framework for your project. Parameter Optimization.

Machine Learning 143

Machine Learning Deep Learning Insurance Modeling 143

CIO Business Intelligence

JANUARY 20, 2023

Topping the list of executive priorities for 2023—a year heralded by escalating economic woes and climate risks—is the need for data driven insights to propel efficiency, resiliency, and other key initiatives. Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need.

Analytics 137

Analytics Key Performance Indicator Unstructured Data Deep Learning 137

CIO Business Intelligence

APRIL 1, 2022

Better decision-making isn’t always about deciding whether A or B is the optimal choice. Consider that it may be easier to make one big decision well, rather than hundreds of smaller decisions that each have different payouts and risks. Sometimes it’s about rethinking what kind of decisions to make. Automation through AI.

Data-driven 98

Data-driven Deep Learning Risk Optimization 98

Domino Data Lab

MARCH 16, 2021

Leaders need to know how to avoid the risk of unethical, biased, or misunderstood models. Lately, however, there is very exciting research emerging around building concepts from first principles with the goal of optimizing the higher layers to be human-readable. It is an active area of research in academia and industry. Saliency Maps.

Modeling 122

Modeling Deep Learning Testing Optimization 122

Smart Data Collective

JULY 8, 2021

With a vast knowledge of previous projects, AI-assisted BIM can come up with the most optimal plan for future ones. By far the biggest advantage of AI implementation in BIM is risk mitigation. AI-assisted BIM could have many benefits for the AEC industries — cost and time efficiency, increased safety, risk mitigation, etc.

Cost-Benefit 131

Cost-Benefit Deep Learning Visualization Modeling 131

CIO Business Intelligence

MARCH 14, 2022

Thus, the storage architecture can be optimized for performance and scale. And by investing in hardware and software solutions that work together to provide optimal performance, real-time data processing environments will continue to scale up and scale out for years to come. Just starting out with analytics?

Data Processing 116

Data Processing Deep Learning Optimization Software 116

CIO Business Intelligence

MARCH 9, 2022

Each ETL step risks introducing failures or bugs that reduce data quality. . Unlike BI, which extracts a small amount of data and for which warehouses are optimized, ML systems process huge datasets using complex, non-SQL code. This dual-system architecture requires continuous engineering to ETL data between the two platforms.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

Smart Data Collective

DECEMBER 9, 2021

The role of accountants is changing to reflect this, with many accountants focusing on analyzing data and gleaning insights from that data , in order to increase efficiency and perform better risk management. AI has the potential to optimize tasks and processes that might otherwise take needless man-hours to handle.

Technology 133

Technology Big Data Machine Learning Deep Learning 133

Smart Data Collective

NOVEMBER 9, 2022

There are a number of great applications of machine learning. One of the biggest benefits is testing processes for optimal effectiveness. The main purpose of machine learning is to partially or completely replace manual testing. Machine learning is used in many industries. Here are the top 8 trusted partners: 1.

Machine Learning 122

Machine Learning Testing Cost-Benefit Data-driven 122

CIO Business Intelligence

JUNE 7, 2022

But only in recent years, with the growth of the web, cloud computing, hyperscale data centers, machine learning, neural networks, deep learning, and powerful servers with blazing fast processors, has it been possible for NLP algorithms to thrive in business environments. Just starting out with analytics?

Unstructured Data 98

Unstructured Data Deep Learning Insurance Interactive 98

IBM Big Data Hub

MAY 9, 2023

Over the past decade, deep learning arose from a seismic collision of data availability and sheer compute power, enabling a host of impressive AI capabilities. But these powerful technologies also introduce new risks and challenges for enterprises. We stand on the frontier of an AI revolution.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

Domino Data Lab

JULY 2, 2019

SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Part of the back-end processing needs deep learning (graph embedding) while other parts make use of reinforcement learning. Software writes Software?

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

CIO Business Intelligence

FEBRUARY 22, 2024

But AI also poses some challenges and risks when it comes to privacy, security, ethics, transparency, and accountability. More processes and tasks are going to be automated, optimized, and personalized with the help of AI, which will mean an increase in productivity, efficiency, and customer and employee satisfaction,” says Prieto.

IT 105

IT Digital Transformation IoT Cost-Benefit 105

AWS Big Data

MAY 16, 2024

Because of this, many organizations are utilizing them as a support geography, aggregating their data to these grids to optimize both their storage and analysis. To learn more details about their benefits, see Introduction to Spatial Indexes. To learn more, visit CARTO.

Data Warehouse 118

Data Warehouse Visualization Cost-Benefit Data-driven 118

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

IBM Big Data Hub

FEBRUARY 13, 2024

Generative AI represents a significant advancement in deep learning and AI development, with some suggesting it’s a move towards developing “ strong AI.” Product development : Generative AI is increasingly utilized by product designers for optimizing design concepts on a large scale.

Enterprise 118

Enterprise Testing Modeling Data-driven 118

Smart Data Collective

MAY 17, 2021

It can also be used to analyze driver behaviors to optimize fuel stops, personal breaks and more. When it comes to fleet maintenance, big data can aid in monitoring vehicle handling and operation to optimize trips, preserve equipment and waylay potential breakdowns. Big data can help by building reliable driver and fleet profiles.

Big Data 132

Big Data Cost-Benefit IoT Machine Learning 132

Smart Data Collective

MARCH 27, 2023

Some of the benefits of AI in banking include: Banks use AI bots to onboard clients and analyze borrower risk. They have also started integrated computer vision and deep learning technology to identify inefficiencies. These tools will be well adapted for sharing data between departments and generally optimizing your operations.

Software 118

Software Finance Cost-Benefit Data-driven 118

Domino Data Lab

JULY 28, 2021

There are many software packages that allow anyone to build a predictive model, but without expertise in math and statistics, a practitioner runs the risk of creating a faulty, unethical, and even possibly illegal data science application. This almost always results in lack of adoption, and can also expose an organization to risk.

Data Science 110

Data Science Statistics Predictive Analytics Recreation/Entertainment 110

Cloudera

OCTOBER 24, 2023

The AI technologies of today—including not just large language models (LLMs) but also deep learning, reinforcement learning, and natural-language processing (NLP) tools—will equip telcos with powerful new automation and analytics capabilities. Learn more about how Cloudera helps Telcos deliver Trusted AI Everywhere.

Interactive 81

Interactive Data-driven Cost-Benefit Optimization 81

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. This unified experience optimizes the process of developing and deploying ML models by streamlining workflows for increased efficiency.

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

IBM Big Data Hub

NOVEMBER 14, 2023

This growth could be internal cost effectiveness, stronger risk compliance, increasing the economic value of a partner ecosystem, or through new revenue streams. Internal data monetization initiatives measure improvement in process design, task guidance and optimization of data used in the organization’s product or service offerings.

Strategy 103

Strategy Data-driven Cost-Benefit Measurement 103

CIO Business Intelligence

APRIL 6, 2022

The risks of a breach are greater as well, from interrupted operations to stiff financial penalties for failing to adhere to industry regulations such as General Data Protection Regulation (GDPR). Real-Time nature of data: The window of opportunity continues to shrink in our digital world. Just starting out with analytics?

Data mining 72

Data mining Deep Learning Insurance Visualization 72

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 90

Unstructured Data Cost-Benefit Machine Learning Experimentation 90