Command-line Tools can be 235x Faster than your Hadoop Cluster (2014)
Hacker News
JANUARY 25, 2024
Adam Drake is an advisor to scale-up tech companies. He writes about ML/AI/crypto/data, leadership, and building tech teams.
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Hacker News
JANUARY 25, 2024
Adam Drake is an advisor to scale-up tech companies. He writes about ML/AI/crypto/data, leadership, and building tech teams.
AWS Machine Learning Blog
APRIL 5, 2024
Among these models, the spatial fixed effect model yielded the highest mean R-squared value, particularly for the timeframe spanning 2014 to 2020. SageMaker Processing enables the flexible scaling of compute clusters to accommodate tasks of varying sizes, from processing a single city block to managing planetary-scale workloads.
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IBM Journey to AI blog
NOVEMBER 2, 2023
Borg’s large-scale cluster management system essentially acts as a central brain for running containerized workloads across its data centers. Omega took the Borg ecosystem further, providing a flexible, scalable scheduling solution for large-scale computer clusters. Control plane nodes , which control the cluster.
AWS Machine Learning Blog
SEPTEMBER 8, 2023
You need permissions to deploy AWS CloudFormation templates, push to the Amazon Elastic Container Registry (Amazon ECR), create Amazon Identity and Access Management (AWS IAM) roles, Amazon Lambda functions, Amazon S3 buckets, Amazon Step Functions, Amazon OpenSearch cluster, and an Amazon Cognito user pool.
IBM Journey to AI blog
NOVEMBER 13, 2023
Developed internally at Google and released to the public in 2014, Kubernetes has enabled organizations to move away from traditional IT infrastructure and toward the automation of operational tasks tied to the deployment, scaling and managing of containerized applications (or microservices ).
AWS Machine Learning Blog
JANUARY 26, 2023
Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed almost 637,000 members to the recently launched Best Egg Financial Health platform, and empowered over 180,000 cardmembers who carry the new Best Egg Credit Card in their wallet.
phData
NOVEMBER 9, 2023
If you go back to 2014, data warehouse platforms were built using legacy architectures that had drawbacks when it came to cost, scale, and flexibility. Effectively this is a way to store the source of truth and build (or rebuild) your downstream data products (including data warehouses) from it. Historically, there were big differences.
AWS Machine Learning Blog
JULY 13, 2023
Amazon SageMaker distributed training jobs enable you with one click (or one API call) to set up a distributed compute cluster, train a model, save the result to Amazon Simple Storage Service (Amazon S3), and shut down the cluster when complete. Finally, launching clusters can introduce operational overhead due to longer starting time.
PyImageSearch
MAY 19, 2025
Each word or sentence is mapped to a high-dimensional vector space, where similar meanings cluster together. exceptions.InsecureRequestWarning) def perform_search(query_text, model_id): """ Perform a search operation using the neural query on the OpenSearch cluster. Figure 3: What Is Semantic Search? disable_warnings(urllib3.exceptions.InsecureRequestWarning)
IBM Journey to AI blog
FEBRUARY 29, 2024
Kubernetes The most popular container orchestration platform is Kubernetes , which was created by Google in 2014 and is still popular for the robust way it automates the deployment of software, enables scalability and supports container management. of this market, while Kubernetes checks in with an 11.52% market share.
Mlearning.ai
APRIL 8, 2023
2014) Significant people : Geoffrey Hinton Yoshua Bengio Ilya Sutskever 5. Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM ” by Deepak Narayanan et al. Use Cases :Language Modeling, Question Answering, Text Generation Significant papers: “Attention is all you need” by Vaswani et al.
Mlearning.ai
APRIL 1, 2023
Doc2Vec was introduced in 2014 by a team of researchers led by Tomas Mikolov. Image taken from Efficient Estimation of Word Representation in Vector Space Top2Vec Top2Vec is an unsupervised machine-learning model designed for topic modelling and document clustering. To achieve this, Top2Vec utilizes the doc2vec model.
Tableau
DECEMBER 1, 2021
Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. June 2014) to give people who understand joins a better experience than a dialog. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation. Connectivity.
AWS Machine Learning Blog
NOVEMBER 16, 2023
Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care. These environments ranged from individual laptops and desktops to diverse on-premises computational clusters and cloud-based infrastructure.
Mlearning.ai
JUNE 8, 2023
Clustering — we can cluster our sentences, useful for topic modeling. Doc2Vec: introduced in 2014, adds on to the Word2Vec model by introducing another ‘paragraph vector’. The article is clustering “Fine Food Reviews” dataset. Enables search to be performed on concepts (rather than specific words).
DagsHub
APRIL 7, 2024
The project was created in 2014 by Airbnb and has been developed by the Apache Software Foundation since 2016. Cloud-agnostic and can run on any Kubernetes cluster. Integration: It can work alongside other workflow orchestration tools (Airflow cluster or AWS SageMaker Pipelines, etc.)
Tableau
DECEMBER 1, 2021
Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. June 2014) to give people who understand joins a better experience than a dialog. Gestalt properties including clusters are salient on scatters. Let’s take a look at each. . Query innovation. Connectivity.
Cambridge Intelligence
JUNE 28, 2023
It’s a busy chart, but I’m drawn to the cluster of larger team nodes in the top left. In 2014, London also hosted the finish of a stage that started in my hometown, Cambridge. Visualizing the Tour de France: the early years Hmmmm. Those “TDF 190# ” don’t look right – they’re clearly not teams – but I know what’s happened.
DrivenData Labs
DECEMBER 11, 2024
Looking back ¶ When we started DrivenData in 2014, the application of data science for social good was in its infancy. The startup cost is now lower to deploy everything from a GPU-enabled virtual machine for a one-off experiment to a scalable cluster for real-time model execution.
Mlearning.ai
MARCH 9, 2023
Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., 2012; Otsu, 1979; Long et al., 2013; Goodfellow et al., Contour detection and hierarchical image segmentation. Goodfellow, I. Shlens, J., & Szegedy, C. Goodfellow, I.
phData
MARCH 29, 2024
Founded in 2014 by three leading cloud engineers, phData focuses on solving real-world data engineering, operations, and advanced analytics problems with the best cloud platforms and products. Over the years, one of our primary focuses became Snowflake and migrating customers to this leading cloud data platform.
Pickl AI
MAY 16, 2023
Skilled in programming languages such as Python, R, and SQL, and have worked on various projects involving predictive modeling, clustering, and classification. Passionate about leveraging data to drive business decisions and improve customer experience.
Cambridge Intelligence
OCTOBER 19, 2023
” First release: 2014 (of Cosmos DB itself) Format: A commercial, hosted, multi-model database with a property graph database service via the Gremlin API Top 3 advantages: A Microsoft Azure service – as part of the Azure family, Cosmos DB’s graph capability comes with SLA-backed speed and throughput, access, and 99.999% availability.
AWS Machine Learning Blog
MAY 7, 2024
Founded in 2014, Veritone empowers people with AI-powered software and solutions for various applications, including media processing, analytics, advertising, and more. Search index creation We use an OpenSearch cluster (OpenSearch Service domain) with t3.medium.search
Explosion
MAY 17, 2023
In 2014 I started working on spaCy , and here’s an excerpt of how I explained the motivation for the library: Computers don’t understand text. We all spend a big part of our working lives writing, reading, speaking and listening. This is unfortunate, because that’s what the web almost entirely consists of.
Explosion
FEBRUARY 18, 2015
This is easy to do, as spaCy loads a vector-space representation for every word (by default, the vectors produced by Levy and Goldberg (2014) _). The only problem is that the list really contains two clusters of words: one associated with the legal meaning of “pleaded”, and one for the more general sense.
AWS Machine Learning Blog
JANUARY 13, 2023
They were admitted to one of 335 units at 208 hospitals located throughout the US between 2014–2015. Finally, monitor and track the FL model training progression across different nodes in the cluster using the weights and biases (wandb) tool, as shown in the following screenshot.
PyImageSearch
OCTOBER 2, 2023
By visualizing this space, colored by clothing type, as shown in Figure 9 , we can discern clusters, patterns, and potential correlations between different attributes. Similar class labels tend to form clusters, as observed with the Convolutional Autoencoder. The torch.nn Auto-Encoding Variational Bayes.
Explosion
FEBRUARY 18, 2015
The tutorial also recommends the use of Brown cluster features, and case normalization features, as these make the model more robust and domain independent. Dependency Parser The parser uses the algorithm described in my 2014 blog post. The following tweaks: I use Brown cluster features — these help a lot; I redesigned the feature set.
Mlearning.ai
FEBRUARY 28, 2023
Year: More than half the cars in the data were manufactured in or after 2014. The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. The log transformation was applied on this column to reduce skewness. I hope you enjoyed this post.
DagsHub
OCTOBER 23, 2024
Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. BLEU on the WMT 2014 English- to-German translation task, improving over the existing best results, including ensembles, by over 2 BLEU. Our model achieves 28.4 after training for 3.5
ODSC - Open Data Science
JANUARY 29, 2024
These outputs, stored in vector databases like Weaviate, allow Prompt Enginers to directly access these embeddings for tasks like semantic search, similarity analysis, or clustering. GANs, introduced in 2014 paved the way for GenAI with models like Pix2pix and DiscoGAN.
Hacker News
JANUARY 9, 2024
The LLMs Have Landed The machine learning superfunctions Classify and Predict first appeared in Wolfram Language in 2014 ( Version 10 ). but with things like clustering). Spreading the power of the Wolfram Language to more and more people and areas.
The MLOps Blog
JANUARY 30, 2025
If training a model takes several months on a large cluster, well only get one shot at a full training run. The 2017 DeepMind study on Population-Based Training (PBT) showcased its potential for LLMs by fine-tuning the f irst transformer model on the WMT 2014 English-German machine translation benchmark.
Towards AI
MAY 12, 2025
This paper pretty much showed everyone how to train deep layers on a GPU 2014: NVIDIA released CuDNN a dedicated CUDA library for Deep Learning. We discuss the GPU memory, the processing cores, the LLM workflows happening inside them & common topologies for clustering. 2008 a landmark paper by Raina et al was released.
OCTOBER 16, 2023
Nagle’s brain implant, developed by the research consortium BrainGate , contained a “Utah” array, a cluster of 100 spiky electrodes that is surgically embedded into the brain. In 2006, Matthew Nagle, a man with spinal cord paralysis, received a brain implant that allowed him to control a computer cursor.
ML Review
MARCH 5, 2019
Well, actually, you’ll still have to wonder because right now it’s just k-mean cluster colour, but in the future you won’t). Within both embedding pages, the user can choose the number of embeddings to show, how many k-mean clusters to split these into, as well as which embedding type to show.
Snorkel AI
MARCH 9, 2023
The project itself debuted in 2014, and has become the infrastructure backbone of many modern software companies and their products. Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. Scaling down the cluster’s size.
Snorkel AI
MARCH 9, 2023
The project itself debuted in 2014, and has become the infrastructure backbone of many modern software companies and their products. Each k8s cluster is made up of two key components: the k8s control plane and an arbitrary number of attached worker nodes whose sole job is to run containers. Scaling down the cluster’s size.
Dataconomy
MAY 26, 2025
Supported platforms Azure Data Studio is compatible with: Windows Linux macOS It supports SQL Server (2014 and later), Azure SQL Database, and Azure SQL Data Warehouse, making it a versatile choice for a range of database environments. This feature is especially useful for working with SQL Server 2019’s big data clusters.
AWS Machine Learning Blog
FEBRUARY 11, 2025
Although GraphStorm can run efficiently on single instances for small graphs, it truly shines when scaling to enterprise-level graphs in distributed mode using a cluster of Amazon Elastic Compute Cloud (Amazon EC2) instances or Amazon SageMaker. Today, AWS AI released GraphStorm v0.4.
AWS Machine Learning Blog
MAY 24, 2023
Batch transform is cost-effective because unlike real-time hosted endpoints that have persistent hardware, batch transform clusters are torn down when the job is complete and therefore the hardware is only used for the duration of the batch job.
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