投稿時間:2023-01-18 04:29:49 RSSフィード2023-01-18 04:00 分まとめ(39件)

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IT	ITmedia 総合記事一覧	[ITmedia News] Intel版「Mac mini」、ひっそりと姿を消す　残るは「Mac Pro」のみに	https://www.itmedia.co.jp/news/articles/2301/18/news075.html	macpro	2023-01-18 03:10:00
AWS	AWS Big Data Blog	Build highly available streams with Amazon Kinesis Data Streams	https://aws.amazon.com/blogs/big-data/build-highly-available-streams-with-amazon-kinesis-data-streams/	Build highly available streams with Amazon Kinesis Data StreamsMany use cases are moving towards a real time data strategy due to demand for real time insights low latency response times and the ability to adapt to the changing needs of end users For this type of workload you can use Amazon Kinesis Data Streams to seamlessly provision store write and read data in a streaming fashion With …	2023-01-17 18:52:41
AWS	AWS Big Data Blog	Build near real-time logistics dashboards using Amazon Redshift and Amazon Managed Grafana for better operational intelligence	https://aws.amazon.com/blogs/big-data/build-near-real-time-logistics-dashboards-using-amazon-redshift-and-amazon-managed-grafana-for-better-operational-intelligence/	Build near real time logistics dashboards using Amazon Redshift and Amazon Managed Grafana for better operational intelligenceAmazon Redshift is a fully managed data warehousing service that is currently helping tens of thousands of customers manage analytics at scale It continues to lead price performance benchmarks and separates compute and storage so each can be scaled independently and you only pay for what you need It also eliminates data silos by simplifying access …	2023-01-17 18:45:34
AWS	AWS Machine Learning Blog	Churn prediction using multimodality of text and tabular features with Amazon SageMaker Jumpstart	https://aws.amazon.com/blogs/machine-learning/churn-prediction-using-multimodality-of-text-and-tabular-features-with-amazon-sagemaker-jumpstart/	Churn prediction using multimodality of text and tabular features with Amazon SageMaker JumpstartAmazon SageMaker JumpStart nbsp is the Machine Learning ML hub of SageMaker providing pre trained publicly available models for a wide range of problem types to help you get started with machine learning Understanding customer behavior is top of mind for every business today Gaining insights into why and how customers buy can help grow revenue nbsp Customer churn is …	2023-01-17 18:49:12
AWS	AWS Management Tools Blog	Visualize and gain insights into your AWS cost and usage with Amazon Managed Grafana	https://aws.amazon.com/blogs/mt/visualize-and-gain-insights-into-your-aws-cost-and-usage-with-amazon-managed-grafana/	Visualize and gain insights into your AWS cost and usage with Amazon Managed GrafanaAs you migrate workloads to AWS and increase consumption of AWS services it becomes critical to have a comprehensive view of the value of AWS as well as to track and effectively manage your AWS cost and usage AWS offer multiple native services such as AWS Cost Explorer AWS Budgets nbsp and AWS Cost Anomaly Detection nbsp to allow …	2023-01-17 18:45:15
AWS	AWS Media Blog	New NFL ‘Expected Return Yards’ stat tackles hidden dynamics of punt and kickoff returns	https://aws.amazon.com/blogs/media/new-nfl-expected-return-yards-stat-tackles-hidden-dynamics-of-punt-and-kickoff-returns/	New NFL Expected Return Yards stat tackles hidden dynamics of punt and kickoff returnsNational Football League NFL fans have all witnessed a returner getting tackled a nanosecond after receiving a punt or kickoff Holding onto the ball let alone gaining a chunk of yardage is a huge win And the odds of a return touchdown are rare But that s exactly why it s a thrill to see a returner …	2023-01-17 18:55:21
AWS	AWS	Define Media: How Define Media Places Ads with Low Latency Using Sophisticated Machine Learning	https://www.youtube.com/watch?v=QJZHs1CSxu0	Define Media How Define Media Places Ads with Low Latency Using Sophisticated Machine LearningDefine Media uses deep neural networks to harness a large amount of data for the ideal ad placement In this episode you will learn how Define Media used managed services from AWS to implement an architecture which made it possible to apply machine learning for ad placement decisions with very low latency Check out more resources for architecting in the AWS​​​cloud ​ AWS AmazonWebServices CloudComputing ThisIsMyArchitecture	2023-01-17 18:32:20
Ruby	Railsタグが付けられた新着投稿 - Qiita	ページネーション	https://qiita.com/uuuDi_97722/items/9db9aa23e5649c0fc114	kaminari	2023-01-18 03:54:25
海外TECH	Ars Technica	RNC loses complaint claiming Gmail spam filter is biased against Republicans	https://arstechnica.com/?p=1910536	filter	2023-01-17 18:16:51
海外TECH	Ars Technica	Din Djarin seeks forgiveness for his sins in The Mandalorian S3 trailer	https://arstechnica.com/?p=1910454	trailer	2023-01-17 18:03:29
海外TECH	MakeUseOf	Error Handling in Go Using the Errors Package	https://www.makeuseof.com/go-error-handling-errors-package/	errors	2023-01-17 18:30:16
海外TECH	MakeUseOf	How to Integrate Grammarly’s Text Editor Into a React Application	https://www.makeuseof.com/react-grammarly-text-editor-integrate/	applicationtake	2023-01-17 18:30:15
海外TECH	MakeUseOf	How to Configure a Windows Hello Fingerprint Login on Windows 11	https://www.makeuseof.com/windows-11-hello-fingerprint-login/	windows	2023-01-17 18:16:16
Apple	AppleInsider - Frontpage News	Apple reclaims smartphone market lead despite 17% contraction	https://appleinsider.com/articles/23/01/17/apple-reclaims-smartphone-market-lead-despite-17-contraction?utm_medium=rss	Apple reclaims smartphone market lead despite contractionGlobal smartphone shipments fell in the holiday quarter versus but the iPhone reclaimed the top spot despite supply issues iPhone The latest report from Canalys reveals that Apple had the highest market share at an increase of year over year In second place Samsung had a market share Read more	2023-01-17 18:52:37
Apple	AppleInsider - Frontpage News	M2 Pro Mac mini versus Mac Studio - compared	https://appleinsider.com/inside/mac-studio/vs/m2-pro-mac-mini-versus-mac-studio---compared?utm_medium=rss	M Pro Mac mini versus Mac Studio comparedThe M Pro Mac mini bridges the gap between entry level and high end Here s how it compares to the baseline Mac Studio Mac Studio next to the Intel Mac miniApple announced a spec bumped Mac mini lineup that supports the M and M Pro processors on January It is the first time the higher chip configuration has come to the tiny desktop thus providing users with more options from low end to high end desktops Read more	2023-01-17 18:46:15
Apple	AppleInsider - Frontpage News	Extended 1 day: Microsoft Office for Mac Home & Business 2021 $24.99 (90% off)	https://appleinsider.com/articles/23/01/14/lowest-price-ever-microsoft-office-for-mac-home-business-2021-2499-90-off?utm_medium=rss	Extended day Microsoft Office for Mac Home amp Business off AppleInsider readers can grab the lowest price ever on a standalone Microsoft Office for Mac Home Business license for one more day Save on Microsoft Office for Mac For a limited time only save on a Microsoft Office Home Business license for Mac Down from the price is courtesy of StackCommerce and valid through Jan Jan only Read more	2023-01-17 18:37:47
Apple	AppleInsider - Frontpage News	M2 Mac mini vs M1 Mac mini - compared	https://appleinsider.com/inside/mac-mini/vs/m2-mac-mini-vs-m1-mac-mini---compared?utm_medium=rss	M Mac mini vs M Mac mini comparedOn January Apple refreshed its Mac mini with the M Apple Silicon processor ーand more Here s how the new M and M Pro models compare to the M Mac mini A relatively early introduction in the year by Apple s usual standards the launch of a refreshed Mac mini in January was unexpected Though Apple didn t just bring out an M Mac mini but also one housing a just launched M Pro chip As the cheapest Mac in the product catalog the new M Mac mini could be easier for users to stomach an upgrade from the M edition than others With the prospect of M Pro performance bonuses that could be even more of a draw Read more	2023-01-17 18:11:37
海外TECH	Engadget	Getty Images sues the maker of AI art generator Stable Diffusion over data scraping allegations	https://www.engadget.com/getty-images-sues-the-maker-of-ai-art-generator-stable-diffusion-over-data-scraping-allegations-184502897.html?src=rss	Getty Images sues the maker of AI art generator Stable Diffusion over data scraping allegationsLast September Getty Images banned the inclusion of AI generated works in its commercial database over copyright concerns On Tuesday Getty Images announced that it is suing Stability AI maker of the popular AI art tool Stable Diffusion in a London court over alleged copyright violations nbsp quot It is Getty Images position that Stability AI unlawfully copied and processed millions of images protected by copyright and the associated metadata owned or represented by Getty Images absent a license to benefit Stability AI s commercial interests and to the detriment of the content creators quot Getty Images wrote in a press statement released Tuesday quot Getty Images believes artificial intelligence has the potential to stimulate creative endeavors quot quot Getty Images provided licenses to leading technology innovators for purposes related to training artificial intelligence systems in a manner that respects personal and intellectual property rights quot the company continued quot Stability AI did not seek any such license from Getty Images and instead we believe chose to ignore viable licensing options and long standing legal protections in pursuit of their stand alone commercial interests quot nbsp The details of the lawsuit have not been made public though Getty Images CEO Craig Peters told The Verge that charges would include copyright and site TOS violations like web scraping Furthermore Peters explained that the company is not seeking monetary damages in this case so as much as it is hoping to establish a favorable precedent for future litigation Text to image generation tools like Stable Diffusion Dall E and Midjourney don t create the artwork that they produce in the same way people do ーthere is no imagination from which these ideas can spring forth Like other generative AI these tools are trained to do what they do using massive databases of annotated images ーthink hundreds of thousands of frog pictures labelled quot frog quot used to teach a computer algorithm what a frog looks like nbsp And why go through the trouble of assembling and annotating a database of your own when there s an entire internet s worth of content there for the taking AI firms like Clearview and Voyager Labs have already tried and been massively repeatedly fined for scraping image data from the public web and social media sites An independent study conducted last August concluded that a notable portion of Stable Diffusion s data was likely pulled directly from the Getty Images site in part as evidenced by the art tool s habit of recreating the Getty watermark nbsp nbsp	2023-01-17 18:45:02
海外TECH	Engadget	Ubisoft staff in Paris will strike over working conditions	https://www.engadget.com/ubisoft-paris-strike-183059140.html?src=rss	Ubisoft staff in Paris will strike over working conditionsIt s Ubisoft s turn to face strikes from unhappy game developers Solidaires Informatique Jeu Vidéo has called for Ubisoft Paris employees to strike on January th to demand better working conditions The labor union wants an quot immediate quot percent salary increase to account for inflation and improved hours that include a four day work week Solidaires Informatique also wants greater transparency on workforce changes as well as pledges to avoid thinly disguised firings and quot abusive quot management practices that push staff to quit The strike plan comes in response to Ubisoft CEO Yves Guillemot s internal email following news the company was cancelling three games and otherwise grappling with tough economic conditions As PC Gamernotes Guillemot called for workers to be quot especially careful quot with spending and warned of moves that included quot targeted restructuring quot and quot natural attrition quot To Solidaires Informatique the executive is attempting to quot shift the blame quot to staff while not so subtly hinting at layoffs pay cuts and quiet studio closures Ubisoft Paris Appel àla grèveVendredi après midiM Guillemot veut mettre la pression àses employés Répondons lui par la grève CALL TO STRIKE FRIDAY th AfternoonM Guillemot want to put pressure on the salaries Let s strike pic twitter com SaSSdwFMーSolidaires Informatique Jeu Vidéo SolInfoJeuVideo January Ubisoft Paris declined to comment to Engadget This isn t the first time Solidaires Informatique has taken Ubisoft to task over its behavior The labor group sued Ubisoft in for allegedly fostering a culture of quot institutional sexual harassment quot where it was easier to tolerate horrible behavior than fix it The company had already fired key managers accused of misconduct but others remained in place The call to action joins a growing labor movement across the gaming world Microsoft just recognized the game industry s largest union while more Activision Blizzard workers are winning union votes That s on top of a gradual turn away from the long hours of crunch time that have often defined game development Eidos Quebec studios started four day weeks in and talent has sometimes left to form independent studios where crunch is forbidden Simply put employees are no longer willing to accept the status quo	2023-01-17 18:30:59
海外TECH	CodeProject Latest Articles	Agent DVR Facial Recognition with CodeProject.AI Server	https://www.codeproject.com/Articles/5349800/Agent-DVR-Facial-Recognition-with-CodeProject-AI-S	server	2023-01-17 18:55:00
海外科学	NYT > Science	Are We Living in a Computer Simulation, and Can We Hack It?	https://www.nytimes.com/2023/01/17/science/cosmology-universe-programming.html	algorithm	2023-01-17 18:56:21
海外科学	NYT > Science	Sickle Cell Cure Brings Mix of Anxiety and Hope	https://www.nytimes.com/2023/01/17/health/sickle-cell-cure-brings-mix-of-anxiety-and-hope.html	Sickle Cell Cure Brings Mix of Anxiety and HopeSome people who have long lived with the disease say they worry about living as a healthy person while others worry about the obstacles to getting treatment	2023-01-17 18:13:37
ニュース	BBC News - Home	Greta Thunberg detained at German coal protest	https://www.bbc.co.uk/news/world-europe-64309628?at_medium=RSS&at_campaign=KARANGA	german	2023-01-17 18:18:31
ニュース	BBC News - Home	O2 Brixton Academy: Security levels in doubt on fatal crush evening	https://www.bbc.co.uk/news/uk-64263074?at_medium=RSS&at_campaign=KARANGA	academy	2023-01-17 18:49:57
ニュース	BBC News - Home	Aaron Ramsdale: Man charged with assaulting Arsenal goalkeeper	https://www.bbc.co.uk/sport/football/64311656?at_medium=RSS&at_campaign=KARANGA	tottenham	2023-01-17 18:26:25
ニュース	BBC News - Home	Scotland Gender Recognition Bill: What are the sticking points?	https://www.bbc.co.uk/news/uk-64304740?at_medium=RSS&at_campaign=KARANGA	constitutional	2023-01-17 18:15:01
ニュース	BBC News - Home	Manchester United: Sir Jim Ratcliffe's company Ineos formally joins process to buy club	https://www.bbc.co.uk/sport/football/64310893?at_medium=RSS&at_campaign=KARANGA	manchester	2023-01-17 18:55:38
ビジネス	ダイヤモンド・オンライン - 新着記事	中高一貫校「東洋英和女学院」がお父さんを魅了するワケ - 中学受験のキーパーソン	https://diamond.jp/articles/-/315152	中学受験	2023-01-18 03:50:00
ビジネス	ダイヤモンド・オンライン - 新着記事	中国の再エネ支配力、OPECの比ではない - WSJ PickUp	https://diamond.jp/articles/-/316221	wsjpickup	2023-01-18 03:45:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「日産の変態経営」、ダイヤモンドの酷評記事に即レスした鮎川義介の釈明（前） - The Legend Interview不朽	https://diamond.jp/articles/-/316184	「日産の変態経営」、ダイヤモンドの酷評記事に即レスした鮎川義介の釈明前TheLegendInterview不朽「ダイヤモンド」年月日号に「日産の変態経営」と題したレポートが掲載された。	2023-01-18 03:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	中南米揺るがす暴動、民主主義に幻滅する市民 - WSJ PickUp	https://diamond.jp/articles/-/316220	wsjpickup	2023-01-18 03:35:00
ビジネス	ダイヤモンド・オンライン - 新着記事	米債券の好調な年明け、寒風和らぐ金融市場 - WSJ PickUp	https://diamond.jp/articles/-/316219	wsjpickup	2023-01-18 03:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「デザイン経営」が効く企業、効かない企業 - デザイン経営の輪郭	https://diamond.jp/articles/-/316136	「デザイン経営」が効く企業、効かない企業デザイン経営の輪郭デザインの力を経営に生かし、企業の競争力の源泉とするー。	2023-01-18 03:25:00
ビジネス	ダイヤモンド・オンライン - 新着記事	人と比べて遅れているからといって気にするな。 「仕事で一人前になる」ための、たった1つのポイント - あなたのビジネスライフは入社3年で決まる	https://diamond.jp/articles/-/315002	著者	2023-01-18 03:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【志麻さんベスト人気レシピ第1位】60兆の細胞が「おいしい」と悲鳴を上げた！ 子どもから大人まで圧倒的人気の【農家の野菜スープ】簡単レシピ［見逃し配信スペシャル］ - 書籍オンライン編集部から	https://diamond.jp/articles/-/316169	野菜スープ	2023-01-18 03:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【英会話上達】 バカでもペラペラになる！ 英会話初心者のための10の心得 - バカでも英語がペラペラ！ 超★勉強法	https://diamond.jp/articles/-/314314	【英会話上達】バカでもペラペラになる英会話初心者のためのの心得バカでも英語がペラペラ超勉強法英語とは縁遠い新潟の片田舎で生まれ育ち、勉強はからっきし苦手。	2023-01-18 03:05:00
ビジネス	ダイヤモンド・オンライン - 新着記事	【共通テストで大失敗】出願校を変えるときの「2つの注意点」 - 逆転合格90日プログラム	https://diamond.jp/articles/-/316246	逆転	2023-01-18 03:03:00
GCP	Cloud Blog	What’s new with Google Cloud	https://cloud.google.com/blog/topics/inside-google-cloud/whats-new-google-cloud/	What s new with Google CloudWant to know the latest from Google Cloud Find it here in one handy location Check back regularly for our newest updates announcements resources events learning opportunities and more  Tip  Not sure where to find what you re looking for on the Google Cloud blog Start here  Google Cloud blog Full list of topics links and resources Week of Jan Jan Cloud CDN now supports private origin authentication for Amazon Simple Storage Service Amazon S buckets and compatible object stores in Preview This capability improves security by allowing only trusted connections to access the content on your private origins and preventing users from directly accessing it Week of Jan Jan Revionics partnered with Google Cloud to build a data driven pricing platform for speed scale and automation with BigQuery Looker and more As part of the Built with BigQuery program this blog post describes the use cases problems solved solution architecture and key outcomes of hosting Revionics product Platform Built for Change on Google Cloud Comprehensive guide for designing reliable infrastructure for your workloads in Google Cloud The guide combines industry leading reliability best practices with the knowledge and deep expertise of reliability engineers across Google Understand the platform level reliability capabilities of Google Cloud the building blocks of reliability in Google Cloud and how these building blocks affect the availability of your cloud resources Review guidelines for assessing the reliability requirements of your cloud workloads Compare architectural options for deploying distributed and redundant resources across Google Cloud locations and learn how to manage traffic and load for distributed deployments Read the full blog here GPU Pods on GKE Autopilot are now generally available Customers can now run ML training inference video encoding and all other workloads that need a GPU with the convenience of GKE Autopilot s fully managed Kubernetes environment Kubernetes v is now generally available on GKE GKE customers can now take advantage of the many new features in this exciting release This release continues Google Cloud s goal of making Kubernetes releases available to Google customers within days of the Kubernetes OSS release Event driven transfer for Cloud Storage Customers have told us they need asynchronous scalable service to replicate data between Cloud Storage buckets for a variety of use cases including aggregating data in a single bucket for data processing and analysis keeping buckets across projects regions continents in sync etc Google Cloud now offers Preview support for event driven transfer serverless real time replication capability to move data from AWS S to Cloud Storage and copy data between multiple Cloud Storage buckets Read the full blog here Pub Sub Lite now offers export subscriptions to Pub Sub This new subscription type writes Lite messages directly to Pub Sub no code development or Dataflow jobs needed Great for connecting disparate data pipelines and migration from Lite to Pub Sub See here for documentation	2023-01-17 20:00:00
GCP	Cloud Blog	Built with BigQuery: How to accelerate data-centric AI development with Google Cloud and Snorkel AI	https://cloud.google.com/blog/products/data-analytics/how-accelerate-data-centric-ai-development-google-cloud-and-snorkel-ai/	Built with BigQuery How to accelerate data centric AI development with Google Cloud and Snorkel AIIn Deloitte s annual “State of AI in the Enterprise survey of business leaders identified AI as critical to their organizations success over the next five years That survey also uncovered a increase in the number of organizations struggling to achieve meaningful AI driven business outcomes Part of this challenge lies in the ability to capitalize on existing data in its various formats spread throughout the organization For example up to of enterprise information assets are scattered across the organization in text PDFs emails web pages and other unstructured formats This includes a wealth of valuable insights embedded within contracts buried within patient files recorded in chat transcripts noted in EHR CRM text fields and present in other formats This wealth of unstructured data is often untapped as some business leaders may be unaware of the value or unsure how to leverage it Challenges The need to put unstructured data to use more rapidly Accessing data across various locations and file types and then operationalizing that data for AI usage is usually a cumbersome manual time consuming and costly process Individually labeling files to build an adequate dataset to train a machine learning ML model is notoriously slow while human errors and inconsistencies also tend to degrade data quality and negatively impact ML model performance  Often analyzing enterprise data requires the expertise of analysts clinicians lawyers or other domain specific experts In highly regulated industries such as financial services and healthcare privacy regulations standards and other access restrictions make the challenges posed in using unstructured data proportionally higher  Solution approachSnorkel AI has teamed with Google Cloud to help organizations transform raw unstructured data into a format that can be used to train actionable AI powered models for insights and decision making By combining Google Cloud services such as BigQuery and Vertex AI with Snorkel AI s data centric AI platform for programmatic data curation and preparation organizations can accelerate AI development x Tapping into the value of unstructured data stored in BigQuery and making that data ready for ML training empowers enterprises to incorporate all types of data for training AI models Snorkel AI s data centric approach unlocks new ways of preparing ML training workloads Snorkel AI addresses one of the biggest blockers to preparing data for AI development the massive hand labeled training datasets needed to prepare data for supervised training of ML models Snorkel AI overcomes this bottleneck through using a programmatic labeling approach implemented in Snorkel Flow a novel data centric AI platform Leveraging business logic and using foundation models as a means of generating labels data science and ML teams can use Snorkel Flow s labeling functions to programmatically label data using various sources including previously labeled datasets that may have been poorly labeled while encoding knowledge or heuristics from subject matter experts Snorkel Flow can leverage these multiple data and knowledge sources to label large quantities of unstructured data at scale  In addition to data scientists other users in the ML lifecycle such as ML engineers can leverage Snorkel Flow to rapidly improve training data quality and model performance using integrated error analysis and model guided feedback mechanisms to develop more accurate AI applications The data centric AI workflow within Snorkel Flow operates as follows Data scientists ML engineers and subject matter experts programmatically label large amounts of data in minutes to hours by creating labeling functions Upon creating labeling functions Snorkel Flow generates a probabilistic labeled dataset that is used to train a model within the platform Next data scientists use guided error analysis to analyze the model s performance deficits They look for the gaps that facilitate creation of more targeted and relevant labeling assignments In other words data scientists and other users specifically work on places where the model is most wrong or on particular high value examples or on commonly confused classes of data Next users collaboratively iterate on these gaps with internal experts refining or adding labeling functions as needed to label even more data with which they can again feed into the model for analysis Users repeat this iteration even after deploying a model and monitoring a slice of production data As a result of this loop the metrics improvements in an AI application are often orders of magnitude greater than what can be achieved with model centric AI and hand labeled data Solution detailsUnified access to data stored on Google CloudWith training data curation and preparation unblocked via programmatic labeling of unstructured data data scientists can harness the full power of Google s end to end BigQuery ML and or Vertex AI platforms to fast track the development of analytics and AI applications Google Cloud customers can easily deploy Snorkel Flow on their Google Cloud infrastructure using Google Kubernetes Engine GKE then consume unstructured semi structured or structured data from Google Cloud data services such as BigQuery and Google Cloud Storage GCS See the below figure for data sources and integrations  BigQuery is a serverless cost effective and cross cloud analytics data warehouse built to address the needs of data driven organizations BigQuery breaks down silos across clouds allowing enterprises to centralize all of their data structured semi structured and unstructured in a single secure repository BigQuery support for unstructured data management includes built in capabilities to secure govern and share unstructured data Snorkel Flow Google Cloud BigQuery The Snorkel Flow platform integrates natively with BigQuery to streamline and simplify AI development With a few clicks data scientists can immediately pull relevant data from BigQuery directly into Snorkel Flow using the integrated BigQuery connector  Data can then be labeled programmatically using a data centric AI workflow in Snorkel Flow to quickly generate high quality training sets over complex highly variable data Snorkel Flow includes templates to classify and extract information from unstructured text native PDFs richly formatted documents HTML data conversational text and more Newly labeled datasets can then be used to either train custom ML models or fine tune pre built models Labeled data can be loaded back into the BigQuery environment as structured data Real world impactTop U S banks healthcare insurance and other Fortune organizations have used Snorkel Flow to extract information from complex documents such as K reports clinical trial protocols technical manuals rent rolls legal contracts and more One Fortune telecom provider and long time Google Cloud customer for example uses Snorkel Flow to classify encrypted network data flows into key application categories Using Snorkel Flow s comprehensive data exploration and error analysis tools the telco successfully trained labels in a matter of hours achieving better accuracy compared to an internal ground truth baseline   Google and Snorkel AI have collaborated on a Snorkel research project for Google s internal use Google used early versions of Snorkel s core technology to tackle data labeling for content product and event classification problems that were not amenable to manual labeling due to the rapid variations in the labels Using Snorkel Google condensed a six month process involving thousands of hand labeled examples into just minutes and built content classification models that achieved an average performance improvement of Better together Snorkel AI Google CloudTogether Google Cloud and Snorkel AI enable Fortune enterprises federal agencies and other AI innovators to operationalize unstructured data to build and and accelerate AI applications to solve their most critical challenges To learn more schedule a custom demo tailored to your use case with Snorkel AI ML experts or watch one of the below recent presentations  Accelerate AI development by eliminating the pain of manual labeling delivered by Snorkel AI co founder Henry Ehernberg as part of a Google Cloud BigQuery Innovation eventPromises and Compromises of Responsible Generative AI Model Adoption in the Enterprise delivered by Google Director Cloud Partner Engineering Dr Ali Arsanjani at Snorkel s Foundation Model Summit  Snorkel AI documented customer results reflect x and similar improvements vs hand labeling   Case study on Google s use of Snorkel s core technology Harnessing Organizational Knowledge for Machine Learning Snorkel DryBell A Case Study in Deploying Weak Supervision at Industrial Scale	2023-01-17 18:30:00