DZone

JANUARY 28, 2025

In the field of machine learning and artificial intelligence, inference is the phase where a trained model is applied to real world data to generate predictions or decisions. Inference Time Compute Inference time compute refers to the amount of computational power required to make such predictions using a trained model.

Artificial Intelligence 162

Artificial Intelligence Processing 162

Sutter's Mill

MARCH 30, 2025

For more background on safety and security issues related to C++, including definitions of language safety and software security and similar terms, see my March 2024 essay C++ safety, in context. This essay picks up our story where that one left off to bring us up to date with a specific focus on undefined behavior (aka UB).

C++ 70

C++ Programming Code Google 70

O'Reilly

APRIL 2, 2025

On April 22, 2022, I received an out-of-the-blue text from Sam Altman inquiring about the possibility of training GPT-4 on OReilly books. And now, of course, given reports that Meta has trained Llama on LibGen, the Russian database of pirated books, one has to wonder whether OpenAI has done the same. We chose one called DE-COP.

Internet 98

Internet Internet Google Testing 98

O'Reilly

DECEMBER 10, 2024

Like OpenAIs GPT-4 o1, 1 its training has emphasized reasoning rather than just reproducing language. GPT-4 o1 was the first model to claim that it had been trained specifically for reasoning. There are more than a few math textbooks online, and its fair to assume that all of them are in the training data.

C++ 102

C++ Design Google Games 102

Dynatrace

JANUARY 21, 2025

Your trained eye can interpret them at a glance, a skill that sets you apart. Ensuring smooth operations is no small feat, whether you’re in charge of application performance, IT infrastructure, or business processes. However, your responsibilities might change or expand, and you need to work with unfamiliar data sets.

Traffic 262

Traffic Metrics Analytics Monitoring 262

O'Reilly

OCTOBER 22, 2024

The way we train juniors, whether it’s at university or in a boot camp or whether they train themselves from the materials we make available to them (Long Live the Internet), we imply from the very beginning that there’s a correct answer. The answer to “what’s the solution” is “it depends.”

Development 133

Development Code Google Engineering 133

DZone

FEBRUARY 25, 2025

We are living in an age where data is of utmost importance, be it analysis or reporting, training data for LLM models, etc. The amount of data we capture in any field is increasing exponentially, which requires a technology that can process large amounts of data in a short duration. One such technology would be Apache Spark.

Java 130

Java Architecture Technology Technology 130

Dynatrace

JUNE 26, 2024

Role -based training requires privacy training alongside security training. FedRAMP increased emphasis on privacy, which takes center stage in Rev.5, 5, including: Configuration Change Control and CM-4 – Impact Analysis now requires privacy impact analysis for configuration changes. FedRAMP Rev.5

Government 279

Government Programming Cloud Innovation 279

O'Reilly

NOVEMBER 19, 2024

Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. See the primary sources “ REALM: Retrieval-Augmented Language Model Pre-Training ” by Kelvin Guu, et al., at Facebook—both from 2020.

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Open Source Database Entertainment Healthcare 125

Dynatrace

JANUARY 17, 2024

And an O’Reilly Media survey indicated that two-thirds of survey respondents have already adopted generative AI —a form of AI that uses training data to create text, images, code, or other types of content that reflect its users’ natural language queries. AI requires more compute and storage. AI performs frequent data transfers.

Strategy 288

Strategy Artificial Intelligence Storage Cloud 288

Dynatrace

MAY 23, 2022

Training & Certification Award, NORAM. Achieving and retaining certifications is an important aspect of partnering with Dynatrace, and our winner of the NORAM Training & Certification Award – Arctiq – has demonstrated continued success in this department. Training & Certification Award, LATAM. RFO of the Year.

Games 246

Games Innovation Energy Cloud 246

The Netflix TechBlog

NOVEMBER 6, 2023

In order to train the model on internal training data (video clips with aligned text descriptions), we implemented a scalable version on Ray Train and switched to a more performant video decoding library. These models are trained on large amounts of image-caption pairs via in-batch contrastive learning.

Media 234

Media Social Media Tuning Engineering 234

Dynatrace

MAY 30, 2023

Training & Certification Award DXC has stood out this year, with 50 individuals becoming Dynatrace Certified across Associate and Professional levels, and this award is a testament to that continued investment in training and enablement with Dynatrace.

Innovation 246

Innovation Cloud AWS DevOps 246

DZone

AUGUST 8, 2024

Snowflake Cortex AL/ML suite helps you train the models to spot and correct these outliers in order to help improve the quality of your results. Anomaly detection is the process of identifying the data deviation from the expected results in a time-series data.

Processing 273

Processing 273

Dynatrace

NOVEMBER 17, 2020

This year, we’ve increased the number of awards to partner individuals to recognize the personal achievements around training, certification, and community participation, along with recognition for partner organizations. EMEA Training and Certification Award. RFO Training and Certification Award. Partner awards. Julius Loman.

Entertainment 244

Entertainment Innovation Virtualization Cloud 244

Dynatrace

JULY 3, 2024

Training and Certification Award “Our APAC partners have excelled in delivering cutting-edge solutions that address the unique demands of the region. Their forward-thinking approach and unwavering commitment to quality and development have been key to our shared success. ” – Alex Lim, senior director APAC partners, Dynatrace.

Innovation 246

Innovation Technology Technology Cloud 246

Dynatrace

JANUARY 30, 2024

Furthermore, AI can significantly boost productivity if employees are properly trained on how to use the technology correctly. “It’s But if you don’t take the time to train the workforce in the programs or the systems you’re bringing online, you lose that effectiveness.

Artificial Intelligence 246

Artificial Intelligence Government Innovation Programming 246

Dynatrace

AUGUST 12, 2024

In evaluating our model’s accuracy in understanding performance/errors and behavior, we use historical real user data and a standard 80-20 train-test split to train our model. It looks at these metrics across key pages to pinpoint where your users are most impacted and which metric directly impacts each page.

Airlines 290

Airlines Metrics Speed Internet 290

DZone

MAY 22, 2023

Given the temporal dependency of the data, traditional validation techniques such as K-fold cross-validation cannot be applied, thereby necessitating unique methodologies for model training and validation.

Strategy 299

Strategy Engineering 299

Dynatrace

JANUARY 4, 2024

It can be difficult to understand the basis of AI systems’ decisions, particularly when they are trained on large and complex data sets. AI systems, and their data, can be biased, either intentionally or unintentionally, reflecting the biases of their creators or the data on which they are trained. AI system bias. Data in context.

Artificial Intelligence 264

Artificial Intelligence Strategy Virtualization Traffic 264

Dynatrace

JUNE 8, 2021

At Dynatrace, our Autonomous Cloud Enablement (ACE) team are the coaches or teach and train our customers to always get the best out of Dynatrace and reach their objectives. Our expert Jean Louis Lormeau suggested a training program to help you become the champion in problem resolution. We can now move to the training phase.

Metrics 242

Metrics Tuning Programming Systems 242

The Netflix TechBlog

FEBRUARY 13, 2023

Training Performance Media model training poses multiple system challenges in storage, network, and GPUs. We have developed a large-scale GPU training cluster based on Ray , which supports multi-GPU / multi-node distributed training. We accomplish this by paving the path to: Accessing and processing media data (e.g.

Media 297

Media Storage Infrastructure Systems 297

Dynatrace

JANUARY 25, 2022

Despite having to reboot Perform 2022 from onsite in Vegas to virtual, due to changing circumstances, we’re still set to offer just the same high-quality training. And, what’s more – Dynatrace offers virtual training year-round in Dynatrace University, our product education platform.

Performance 246

Performance Virtualization Education Analytics 246

Dynatrace

JANUARY 31, 2024

Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. The LLM then synthesizes the retrieved data with the augmented prompt and its internal training data to create a response that can be sent back to the user. million AI server units annually by 2027, consuming 75.4+

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Cache Azure Infrastructure Monitoring 276

The Netflix TechBlog

NOVEMBER 13, 2023

Practical use cases for speech & music activity Audio dataset preparation Speech & music activity is an important preprocessing step to prepare corpora for training. Content, genre and languages Instead of augmenting or synthesizing training data, we sample the large scale data available in the Netflix catalog with noisy labels.

Architecture 233

Architecture Energy Benchmarking Processing 233

The Netflix TechBlog

NOVEMBER 11, 2022

In semi-supervised anomaly detection models, only a set of benign examples are required for training. Data Data Labeling For the task of anomaly detection in streaming platforms, as we have neither an already trained model nor any labeled data samples, we use structural a priori domain-specific rule-based assumptions, for data labeling.

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C++ Metrics Tuning Strategy 321

DZone

MARCH 1, 2024

This streamlines the process of building AI-powered APIs by reducing the need for manual intervention in model training and deployment. Key Trends and Advancements AutoML for APIs AutoML (Automated Machine Learning) tools are increasingly being used to automate the development of machine learning models that can be exposed through APIs.

Healthcare 263

Healthcare Technology Technology Processing 263

DZone

MAY 7, 2023

It’s a shorter version of a ScyllaDB University (self-paced free training) lab. The following tutorial walks you through how to use Spring Boot apps with ScyllaDB for time series data, taking advantage of shard-aware drivers and prepared statements.

Storage 285

Storage Servers Testing 285

The Netflix TechBlog

DECEMBER 17, 2024

Training: We created easy-to-provide feedback using and with a fully integrated fine-tuning loop to allow end-users to teach new domains and questions around it effectively. For example, LORE provides human-readable reasoning on how it arrived at the answer that users can cross-verify.

Analytics 212

Analytics Engineering Entertainment Metrics 212

Dynatrace

APRIL 26, 2023

One effective capacity-management strategy is to switch from a reactive approach to an anticipative approach: all necessary capacity resources are measured, and those measurements are used to train a prediction model that forecasts future demand. You can use any DQL query that yields a time series to train a prediction model.

Games 246

Games Analytics Strategy Cloud 246

The Netflix TechBlog

NOVEMBER 17, 2022

During training, our goal is to generate the best downsampled representation such that, after upscaling, the mean squared error is minimized. We focus on a robust downscaler that is trained given a conventional upscaler, like bicubic. We focus on a robust downscaler that is trained given a conventional upscaler, like bicubic.

Network 300

Network Media Innovation Serverless 300

Dynatrace

AUGUST 8, 2024

Employee training in cybersecurity best practices and maintaining up-to-date software and systems are also crucial. Comprehensive training programs and strict change management protocols can help reduce human errors. Possible scenarios An IT technician accidentally deletes a critical database, causing a service outage.

Software 290

Software Software Infrastructure Network 290

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. Because IT systems change often, AI models trained only on historical data struggle to diagnose novel events. That’s where causal AI can help.

Government 263

Government Analytics Benchmarking Storage 263

The Netflix TechBlog

JUNE 20, 2023

To address the first challenge, we use pre trained sentence-level embeddings, e.g. from an embedding model optimized for paraphrase identification , to represent text in both sources. In order to leverage this noisily aligned data source, we need to align time-stamped text (e.g.

Benchmarking 262

Benchmarking C++ Availability Programming 262

Dynatrace

SEPTEMBER 30, 2021

By carving the right AWS certification path, developers can even use their certification and training to advance their careers long term. What is the value of AWS training and certification? You and your peers – if you team up – can benefit on multiple levels from AWS training and certification.

AWS 246

AWS Best Practices Cloud Analytics 246

Dynatrace

DECEMBER 30, 2021

With real-time causal AI, organizations can identify the root cause of issues without having to train their data models up front. That’s critical to circumvent the time-consuming process of training algorithms to understand system behavior. Traditional machine learning approaches involve time-consuming training of algorithms.

Strategy 264

Strategy Energy Cloud Innovation 264

The Netflix TechBlog

MARCH 7, 2024

In addition to Spark, we want to support last-mile data processing in Python, addressing use cases such as feature transformations, batch inference, and training. There are several ways to provide explainability to models but one way is to train an explainer model based on each trained model.

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Systems Media Cache Open Source 235