The Morning Paper

AUGUST 25, 2019

Snuba: automating weak supervision to label training data Varma & Ré, VLDB 2019. It’s tackling the same fundamental problem: how to gather enough labeled data to train a model, and how to effectively use it in a weak supervision setting (supervised learning with noisy labels). It took me quite a while to get my head around this!

Logistics 76

Logistics Efficiency Design Network 76

The Netflix TechBlog

FEBRUARY 13, 2023

This feature store is equipped with a data replication system that enables copying data to different storage solutions depending on the required access patterns. Training Performance Media model training poses multiple system challenges in storage, network, and GPUs.

Media 290

Media Storage Infrastructure Systems 290

Dynatrace

JANUARY 4, 2024

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. 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. That’s where causal AI can help.

Government 205

Government Analytics Benchmarking Storage 205

Dynatrace

JANUARY 17, 2024

An AI observability strategy—which monitors IT system performance and costs—may help organizations achieve that balance. Training AI data is resource-intensive and costly, again, because of increased computational and storage requirements. AI requires more compute and storage. AI performs frequent data transfers.

Strategy 227

Strategy Artificial Intelligence Storage Cloud 227

Dynatrace

JANUARY 31, 2024

GenAI is prone to erratic behavior due to unforeseen data scenarios or underlying system issues. Augmenting LLM input in this way reduces apparent knowledge gaps in the training data and limits AI hallucinations. But energy consumption isn’t limited to training models—their usage contributes significantly more.

Cache 209

Cache Azure Infrastructure Monitoring 209

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 218

Innovation Cloud AWS DevOps 218

The Morning Paper

SEPTEMBER 14, 2020

Aligning superhuman AI with human behavior: chess as a model system , McIlroy-Young et al., As well as outright behaviour and performance once fully trained, a related interesting question is whether or not the AI model improves with training in the same way that humans do on the same task as their skill levels increase.

Systems 85

Systems Games Engineering Open Source 85

Dynatrace

MARCH 13, 2024

The Network and Information Systems 2 (NIS2) Directive, which goes into effect in Oct 2024, aims to enhance the security of network and information systems throughout the EU. NIS2 is an evolution of the Network and Information Systems (NIS) Security Directive, which has been in effect since 2016.

Best Practices 233

Best Practices Education Strategy Analytics 233

The Morning Paper

FEBRUARY 16, 2020

Migrating a privacy-safe information extraction system to a software 2.0 This is a comparatively short (7 pages) but very interesting paper detailing the migration of a software system to a ‘Software 2.0’ we spend the majority of our effort on writing code, expressing how the system achieves its goals.

Systems 84

Systems Design Software Software 84

All Things Distributed

MARCH 12, 2018

At Amazon, we are heavily invested in machine learning (ML), and are developing new tools to help developers quickly and easily build, train, and deploy ML models. The interfaces to our digital system have been dictated by the capabilities of our computer systems—keyboards, mice, graphical interfaces, remotes, and touch screens.

Systems 110

Systems AWS Games Transportation 110

DZone

SEPTEMBER 11, 2023

False positives are instances where the system incorrectly identifies a regular event as an anomaly, leading to unnecessary investigative efforts and operational delays. Overview of the System Architecture Data Stream This is the continuous flow of data that the engine reviews.

Engineering 161

Engineering Healthcare Architecture Monitoring 161

O'Reilly

OCTOBER 30, 2023

These include: What data sources the model is trained on. The recent discovery (documented by an exposé in The Atlantic ) that OpenAI, Meta, and others used databases of pirated books, for example, highlights the need for transparency in training data. Policy on use of user data for further training. Operational Metrics.

Energy 117

Energy Internet Internet Metrics 117

The Morning Paper

JUNE 6, 2019

Towards federated learning at scale: system design Bonawitz et al., This is a high level paper describing Google’s production system for federated learning. Federated Learning (FL) is a distributed machine learning approach which enables training on a large corpus of decentralized data residing on devices like mobile phones.

Systems 71

Systems Design Google Servers 71

DZone

JULY 21, 2021

Systems Engineering is the discipline of integrating parts into a functioning whole. In the early 2000s, members of the International Council on Systems Engineering (INCOSE) and the Object Management Group (OMG) joined together to create a graphical modeling language that was tailored to the needs of systems engineers.

Engineering 246

Engineering Systems Design Software 246

The Morning Paper

SEPTEMBER 26, 2019

Wireless attacks on aircraft instrument landing systems Sathaye et al., Today’s paper is a good reminder of just how important it is becoming to consider cyber threat models in what are primary physical systems, especially if you happen to be flying on an aeroplane – which I am right now as I write this! A quick primer on ILS.

Wireless 91

Wireless Systems Airlines Hardware 91

The Netflix TechBlog

NOVEMBER 11, 2022

In semi-supervised anomaly detection models, only a set of benign examples are required for training. Streaming Platforms Commercial streaming platforms shown in Figure 1 mainly rely on Digital Rights Management (DRM) systems. a browser) is normally matched with a certain DRM system (e.g.,

C++ 312

C++ Metrics Tuning Strategy 312

Dynatrace

DECEMBER 30, 2021

Organizations need automatic intelligence to identify the root cause of cloud systems’ performance and security issues. The goal is to identify issues before they affect system performance or user experience. But that’s a tall order when organizations have assembled a web of interconnected and sometimes ephemeral IT systems.

Strategy 228

Strategy Energy Cloud Innovation 228

Dynatrace

APRIL 22, 2024

Predictive AI uses data collection, algorithm assignment, and model training for user behavior prediction, demand forecasting, fraud detection, and quality control, among other areas. These help teams with data augmentation, anomaly detection, simulation, and documentation, among other areas.

Software 173

Software Software Artificial Intelligence Development 173

The Netflix TechBlog

MARCH 14, 2023

Much of the ML literature focuses on model training, evaluation, and scoring. We implemented a batch processing system for users to submit their requests and wait for the system to generate the output. This limited pilot system greatly reduced the time spent by our users to manually analyze the content.

Media 291

Media Innovation Energy Architecture 291

Dynatrace

JUNE 8, 2021

In software we use the concept of Service Level Objectives (SLOs) to enable us to keep track of our system versus our goals, often shown in a dashboard – like below –, to help us to reach an objective or provide an excellent service for users. The training program to proactively improve your services. Are you ready to kick some bugs?

Metrics 170

Metrics Tuning Programming Systems 170

O'Reilly

MARCH 26, 2024

TL;DR LLMs and other GenAI models can reproduce significant chunks of training data. Specific prompts seem to “unlock” training data. Generative AI Has a Plagiarism Problem ChatGPT, for example, doesn’t memorize its training data, per se. This is the basis of The New York Times lawsuit against OpenAI. They are dream machines.

Artificial Intelligence 108

Artificial Intelligence Social Media Google Internet 108

Dynatrace

JANUARY 22, 2024

That’s why causal AI use cases abound for organizations looking to build more reliable and transparent AI systems. Understanding complex systems Causal AI holds great importance for achieving full-stack observability in complex systems. More generally, causal AI can contribute to explainable and fair AI systems.

Artificial Intelligence 213

Artificial Intelligence Healthcare Retail Government 213

Brendan Gregg

JULY 15, 2019

BPF (eBPF) tracing is a superpower that can analyze everything, and I'll show you how in my upcoming book BPF Performance Tools: Linux System and Application Observability , coming soon from Addison Wesley. A time where you can pose arbitrary questions of the system, and it can answer them.

Systems 111

Systems Performance Education Technology 111

Dynatrace

DECEMBER 13, 2023

That’s why many organizations are turning to generative AI—which uses its training data to create text, images, code, or other types of content that reflect its users’ natural language queries—and platform engineering to create new efficiencies and opportunities for innovation. Technology prediction No. Technology prediction No.

Technology 208

Technology Technology Artificial Intelligence Analytics 208

Dynatrace

MARCH 29, 2024

Others involve introducing new threats as AI becomes more integrated into IT systems as a whole. Generative AI: A type of AI that uses an algorithm trained on large amounts of data collected from diverse sources to generate various types of content, including text, images, audio, and synthetic data.

Artificial Intelligence 188

Artificial Intelligence DevOps Strategy Open Source 188

Dynatrace

OCTOBER 17, 2022

Anomalous behavior in a newly deployed application can easily escape human detection, but AIOps systems complement SecOps engineers by identifying and reporting on potentially exploitable vulnerabilities. This process continues until the system identifies a root cause. The four stages of data processing. Two types of root cause.

DevOps 202

DevOps Artificial Intelligence Healthcare Innovation 202

O'Reilly

DECEMBER 12, 2023

Another group of cases involving text (typically novels and novelists) argue that using copyrighted texts as part of the training data for a Large Language Model (LLM) is itself copyright infringement, 1 even if the model never reproduces those texts as part of its output. Is an artist’s style copyrightable, and if so, what does that mean?

Artificial Intelligence 99

Artificial Intelligence Media Google Processing 99

Dynatrace

JUNE 14, 2023

This digital transformation journey requires AI-powered answers and intelligent automation that legacy systems can’t deliver. The Services Endorsement Program includes training and certification for partners that span unified observability and security, AIOps, and advanced DevSecOps and CloudOps.

Programming 185

Programming Analytics Innovation Best Practices 185

The Morning Paper

JUNE 9, 2019

PyTorch-BigGraph: a large-scale graph embedding system Lerer et al., Once the graph is partitioned a distributed execution model becomes possible to speed up training. Using 8 machines decreased training time by a factor of 4, and memory consumption was reduced by 88%. RESCAL, DistMult, TransE, ComplEx) can be trained.

Systems 60

Systems Network Efficiency Servers 60

Dynatrace

FEBRUARY 26, 2024

During the Dynatrace annual user conference, Perform , the Partner Summit session returned, welcoming Global System Integrators (GSIs), Hyperscalers, and Cloud Solutions Partners to participate.

Artificial Intelligence 199

Artificial Intelligence IoT Programming Innovation 199

Dynatrace

DECEMBER 4, 2023

By using OpenLLMetry and Dynatrace, anyone can get complete visibility into their system, including gen-AI parts with 5 minutes of work.” Data quality and drift: Monitoring the quality and characteristics of training and runtime data to detect significant changes that might impact model accuracy.

Open Source 262

Open Source Latency Metrics Java 262

Dynatrace

OCTOBER 14, 2022

These systems are generating more data than ever, and teams simply can’t keep up with a manual approach. Artificial intelligence (AI) refers to a system’s ability to mimic human cognitive function. Machine learning applications may be developed standalone, but they’re often part of larger AI systems.

Artificial Intelligence 180

Artificial Intelligence DevOps Analytics Cloud 180

The Netflix TechBlog

APRIL 26, 2022

We built Axion primarily to remove any training-serving skew and make offline experimentation faster. We make sure there is no training/serving skew by using the same data and the code for online and offline feature generation. Our machine learning models train on several weeks of data. What’s our end goal?

Storage 187

Storage Design Scalability Latency 187

The Netflix TechBlog

OCTOBER 18, 2022

These include ETL pipelines, ML model training workflows, batch jobs, etc. Due to its popularity, the number of workflows managed by the system has grown exponentially. The scheduler on-call has to closely monitor the system during non-business hours. A large number of batch workflows run daily to serve various business needs.

Java 202

Java Scalability Traffic Architecture 202

High Scalability

DECEMBER 16, 2022

Cloud computing has become a widely-used model of computing, as it offers a number of benefits over traditional, on-premises computing systems. I'm sorry, but as a large language model trained by OpenAI, I don't have the ability to browse the internet or keep up-to-date with current events. Can you expand? Are you hosted on the cloud?

Cloud 201

Cloud Serverless Internet Internet 201

Dynatrace

JULY 20, 2022

Artificial intelligence (AI) has been a hot topic among federal agencies as government IT leaders look to modernize their systems to help solve complex challenges. In addition to the lack of staff knowledge about AI, our research identified a need for training as an obstacle for 32% of participants. Dynatrace news.

Artificial Intelligence 217

Artificial Intelligence Government Strategy Website 217

Dynatrace

JULY 24, 2023

Unlike correlation-based machine learning, which calculates probabilities based on statistics, causal AI uses fault-tree analysis to determine system-level failures based on component-level failures. Such an outcome could be a CPU spike that progresses into a system failure. ” The post What is causal AI?

Artificial Intelligence 221

Artificial Intelligence Analytics Network Metrics 221