O'Reilly

NOVEMBER 28, 2023

A year after the first web servers became available, how many companies had websites or were experimenting with building them? Training models and developing complex applications on top of those models is becoming easier. report that the difficulty of training a model is a problem. Certainly not two-thirds of them.

Open Source 106

Open Source Artificial Intelligence Google Infrastructure 106

Dynatrace

JULY 6, 2022

More than half of all respondents cited two key SRE adoption barriers: the perceived difficulty of training existing IT professionals in SRE best practices, and the cost and difficulty of finding skilled professionals. Design, implement, and tune effective SLOs. Make SRE accessible. Apply AIOps for analysis and automation.

Best Practices 193

Best Practices Open Source Tuning Infrastructure 193

All Things Distributed

MARCH 19, 2018

For example, training on more data means more accurate models. Last re:Invent, to make the problem of authoring, training, and hosting ML models easier, faster, and more reliable, we launched Amazon SageMaker. Machine learning models are usually trained tens or hundreds of times. In machine learning, more is usually more.

Scalability 159

Scalability Hardware AWS Tuning 159

Percona

MARCH 23, 2023

Typically a good value is 70%-80% of available memory. If you see concurrency issues, you can tune this variable. Innodb_io_capacity (Dynamic) – It defines the number of I/O operations per second (IOPS) available to InnoDB background tasks, such as flushing pages from the buffer pool and merging data from the change buffer.

Performance 123

Performance Hardware Tuning Storage 123

The Netflix TechBlog

OCTOBER 18, 2022

These include ETL pipelines, ML model training workflows, batch jobs, etc. Meson was based on a single leader architecture with high availability. Similarly, ML model training workflows usually consist of tens of thousands of training jobs within a single workflow. With the high growth of workflows in the past few years?

Java 202

Java Scalability Traffic Architecture 202

All Things Distributed

NOVEMBER 29, 2017

Though the AWS Cloud gives you access to the storage and processing power required for ML, the process for building, training, and deploying ML models has unique challenges that often block successful use of this powerful new technology. The challenges begin with collecting, cleaning, and formatting training data.

Tuning 94

Tuning AWS Scalability Infrastructure 94

Percona

DECEMBER 27, 2023

All of the database automation for running a highly available, resilient, and secure database is built into the operator to simplify the operation and management of your clusters. This fully automated scaling and tuning will enable a serverless-like experience in our Operators and Everest.

Cloud 77

Cloud Open Source Strategy Best Practices 77

O'Reilly

MAY 9, 2023

Using AI means auditing the outputs of AI systems to ensure that they’re fair; it means documenting the behaviors of AI models and training data sets so that users know how the data was collected and what biases are inherent in that data. Its training data and its design must both be well documented and available to the public.

Infrastructure 84

Infrastructure Government Design Tuning 84

Dynatrace

DECEMBER 2, 2021

These can include business metrics, such as conversion rates, uptime, and availability; service metrics, such as application performance; or technical metrics, such as dependencies to third-party services, underlying CPU, and the cost of running a service. availability of a website over a year, your error budget is.05%. How SLOs work.

Metrics 196

Metrics Best Practices DevOps Infrastructure 196

Percona

NOVEMBER 3, 2023

Have you tuned your environment? This entails providing comprehensive training for your staff, equipping them with both foundational and sophisticated testing methodologies. Additionally, it involves the acquisition or development of specialized testing software, which often comes with its own set of training requirements.

Database 81

Database Open Source Benchmarking Strategy 81

Scalegrid

JANUARY 11, 2024

Read also – Enterprise Cloud Security Strategy For 2024 Cloud Security Monitoring Tools and Techniques When it comes to monitoring cloud security, we have a wide range of tools and techniques available. Proactive monitoring capabilities are also available, along with detailed reports on databases and clusters.

Best Practices 130

Best Practices Cloud Monitoring Strategy 130

O'Reilly

APRIL 4, 2024

In the case of artificial intelligence, training large models is indeed expensive, requiring large capital investments. OpenAI, for example, has trained not just on publicly available data but reportedly on copyrighted content retrieved from pirate sites. But those investments demand commensurately large returns.

Artificial Intelligence 60

Artificial Intelligence Open Source Innovation Transportation 60

Percona

MAY 15, 2023

Those that have or would like to sign up for a Percona Support Subscription will continue to receive operational support and services.

Servers 106

Servers Open Source Tuning Software 106

The Netflix TechBlog

AUGUST 17, 2023

Each algorithm needed a process of evaluation and tuning to get great results in AVA Discovery View. This feedback is easily accessible by our algorithm partners and used in training improved versions of the models. Discovery View is available via Studio Gateway for AVA UI and other front-end applications to leverage.

Media 169

Media Scalability Architecture Strategy 169

Sutter's Mill

JUNE 17, 2023

Instead, the subgroups are a three-stage pipeline and continue concurrently working on new feature development all the time, and the feature freezes are just the checkpoints where we pause loading new features into this particular train.

C++ 143

C++ Programming Tuning Design 143

The Morning Paper

JULY 7, 2019

The success of ML-centric projects depends heavily on data availability, quality, and management. Models have a provenance tag explaining which data it has been trained on and which version of the model was used. ” Microsoft teams found a need to blend traditional data management tools with their ML frameworks and pipelines.

Software Engineering 92

Software Engineering Engineering Software Software 92

O'Reilly

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. Note that the dataset on which GPT-3 trained terminated around October 2019. OpenAI’s text generating system GPT-3 has captured mainstream attention.

Social Media 136

Social Media Media Internet Internet 136

Adrian Cockcroft

JUNE 21, 2022

I also learned how marketing worked, and began to build my presentation and training skills as I was sent around the world by Sun to teach workshops and speak at events. I still code in R… One role I had for many years was to lead technical training events for the global specialist systems engineers, which we called the Ambassador Program.

Tuning 52

Tuning Benchmarking Engineering C++ 52

All Things Distributed

NOVEMBER 30, 2016

Effectively applying AI involves extensive manual effort to develop and tune many different types of machine learning and deep learning algorithms (e.g. automatic speech recognition, natural language understanding, image classification), collect and clean the training data, and train and tune the machine learning models.

AWS 165

AWS Lambda Artificial Intelligence Mobile 165

The Morning Paper

JUNE 4, 2019

” That’s trillions of training and serving examples per day, across more than 700 machine learning pipelines. An ML model is trained daily on batches of data, with real queries from the previous day joined with labels to create the next day’s training data. Breck et al. Testing one batch of data.

Google 92

Google Code Infrastructure Best Practices 92

Sutter's Mill

NOVEMBER 11, 2023

This week’s meeting: Meeting #2 of C++26 At the previous meeting in June, the committee adopted the first 40 proposed changes for C++26, including many that had been ready for a couple of meetings and were just waiting for the C++26 train to open to be adopted. The updated paper will be available in the next mailing in mid-December.

C++ 107

C++ Lambda Network Programming 107

The Morning Paper

OCTOBER 8, 2019

The core application of machine learning discussed in this paper is the model which orders available listings according to a guest’s likelihood of booking. Note that the Airbnb team already had experience with machine learning, data pipelines in place, and an online controlled experiment platform available. Tuning the model.

Network 82

Network Architecture Tuning Traffic 82

The Morning Paper

JUNE 27, 2019

Performance on accelerators matters because almost all current machine learning research, and most training of production models, uses them. Our interpretation of these results is that current frameworks excel at workloads where it makes sense to manually tune the small set of computations used by a particular model or family of models.

Systems 87

Systems Tuning Programming Innovation 87

Enprowess

MAY 10, 2018

As Artificial intelligence and Machine learning are in action now, there are various APIs and libraries available with Java too. An easy, fast and fun way to get started with it is – Automation of tag assignments in Liferay on uploaded images based on a pre-trained model. Training a model with updates. libtensorflow-1.8.0.jar.

Artificial Intelligence 52

Artificial Intelligence Open Source Google Java 52

Dynatrace

JANUARY 13, 2021

Dynatrace monitoring-as-code allows us to do just that – and what started around one year ago in a ‘Minimal Viable Product’ approach to cover our internal needs, is now available to all our customers as Open Source on GitHub. Stay tuned for an upcoming Performance Clinic ! and some sample configurations used for integration testing.

Open Source 140

Open Source Code Monitoring Azure 140

Percona

OCTOBER 18, 2023

Resource allocation: Personnel, hardware, time, and money The migration to open source requires careful allocation (and knowledge) of the resources available to you. Does anyone on my team require further training before we start? Performance tuning The first critical move in performance tuning is query optimization.

Open Source 89

Open Source Database Hardware Strategy 89

Adrian Cockcroft

NOVEMBER 26, 2023

Programs like Open Data on AWS provide free, publicly available datasets, accelerating sustainability innovation. In this session, find out how AWS customers are using open data and AWS’s broad range of compute, AI/ML, and database services to build sustainability workloads in the cloud. AWS speakers: Wafae Bakkali, Isha Dua

AWS 52

AWS Energy IoT Best Practices 52

The Morning Paper

JUNE 13, 2019

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. As a transition from the SysML papers we’ve been looking at recently, I’ve chosen a HotOS position paper from the Stanford Platform Lab to kick things off.

Hardware 58

Hardware Latency Serverless Energy 58

O'Reilly

JULY 25, 2023

I guessed that maybe ChatGPT only knew about v2 since it was trained on open-source code from before September 2021 (its knowledge cutoff date) and v2 was the dominant format before that date. To my surprise, it knew about v3 from its training data and generated a v3 manifest file for me in response. But still, I liked how Moment.js

Programming 98

Programming Code Design Benchmarking 98

O'Reilly

OCTOBER 11, 2022

The data available to our retail business is much more limited. What would happen to product design, sales, and engineering if a constant digest of issues from customer service were available to them? Was it trained using biased, unfair data? Is special-purpose training to fine-tune a model’s behavior an option?

Games 114

Games Healthcare Processing Retail 114

Adrian Cockcroft

NOVEMBER 13, 2023

I’ve written before about how to tune out retry storms. Then that capacity is then offered on the spot market, which lowers the spot price, and someone uses those instances for an opportunistic CPU intensive workload like crypto or AI training, which they only run when the cost is very low.

Energy 52

Energy Cloud Traffic Transportation 52

IO River

NOVEMBER 15, 2023

Two of them are particularly gnarly: fine-tuning rules to perfection and managing a WAF over a multi-CDN architecture. ‍Think of it as the captain of a well-trained squad, each member with a specialized skill set. Imagine you have a special promotion only available to customers in a particular country. It's that precise.‍WAF

Traffic 52

Traffic Network Logistics Architecture 52

The Morning Paper

JULY 16, 2019

To investigate all this the authors take six recent unsupervised disentanglement methods, train them over seven different data sets, and evaluate them using six different disentanglement measures. The result is a corpus of more than 10,000 trained models. Luck and tuning.

Logistics 43

Logistics Metrics Network Strategy 43

IO River

NOVEMBER 2, 2023

Two of them are particularly gnarly: fine-tuning rules to perfection and managing a WAF over a multi-CDN architecture. Think of it as the captain of a well-trained squad, each member with a specialized skill set. Let's dive deep into these challenges.‍1.

Traffic 40

Traffic Network Logistics Architecture 40

SQL Performance

MAY 7, 2019

These threads are created when SQL Server starts, depending on the number of processor cores available for SQL Server to use. The waiter list , which has all the threads that are basically stuck, waiting for a particular resource to become available. Tracking Waits Using SentryOne Tools.

Servers 40

Servers Azure Metrics Tuning 40

Smashing Magazine

SEPTEMBER 6, 2021

As such, a micro-optimization is, again, how you probably need to fine-tune things on a low level to really benefit from it. I would personally recommend using Cloudflare or Fastly because they have been intimately involved in the standardization process and will have the most advanced and well-tuned implementations available.

Network 105

Network Servers Cache Traffic 105

Smashing Magazine

AUGUST 22, 2021

Additionally, even if we knew the available physical bandwidth, that wouldn’t mean we could use all of it ourselves. Several users are typically active on a network concurrently, each of whom need a fair share of the available bandwidth. More in-depth information is available. What Does It All Mean?

Performance 106

Performance Network Latency Servers 106