投稿時間:2023-02-02 07:18:13 RSSフィード2023-02-02 07:00 分まとめ(23件)

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IT	ITmedia 総合記事一覧	[ITmedia News] ChatGPTの有料サブスク版「Plus」、月額20ドルで提供開始	https://www.itmedia.co.jp/news/articles/2302/02/news083.html	chatgpt	2023-02-02 06:39:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 人口815人の村を「AR貞子」が救う？　奈良県・下北山村がだいぶ思い切ったコラボを決めたワケ	https://www.itmedia.co.jp/business/articles/2302/02/news051.html	itmedia	2023-02-02 06:30:00
IT	ビジネス+IT 最新ニュース	全自動かつ短時間でラボ環境構築、「Jumpstart HCIBox」のスゴさとは	https://www.sbbit.jp/article/cont1/105901?ref=rss	azurearcjumpstart	2023-02-02 06:10:00
Google	カグア！Google Analytics 活用塾:事例や使い方	ポッドキャストで直接的な収益化方法はいくつもある	https://www.kagua.biz/marke/podcast/20211019a1.html	applepodcast	2023-02-01 21:00:36
AWS	AWS Big Data Blog	How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics	https://aws.amazon.com/blogs/big-data/how-amazon-devices-scaled-and-optimized-real-time-demand-and-supply-forecasts-using-serverless-analytics/	How Amazon Devices scaled and optimized real time demand and supply forecasts using serverless analyticsEvery day Amazon devices process and analyze billions of transactions from global shipping inventory capacity supply sales marketing producers and customer service teams This data is used in procuring devices inventory to meet Amazon customers demands With data volumes exhibiting a double digit percentage growth rate year on year and the COVID pandemic disrupting global logistics …	2023-02-01 21:35:28
AWS	AWS	Perform Common Operations on an Amazon MSK Cluster | Amazon Web Services	https://www.youtube.com/watch?v=AUx5x_jrX6I	Perform Common Operations on an Amazon MSK Cluster Amazon Web ServicesIn this video you ll see how to perform common operations on an Amazon MSK cluster With Amazon Managed Streaming for Apache Kafka Amazon MSK you can efficiently launch and expand a cluster configure auto scaling and security settings and update cluster configurations For more information on this topic please visit the resource s below Subscribe More AWS videos More AWS events videos ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster streaming datastreaming apache kafka cloud AWS AmazonWebServices CloudComputing	2023-02-01 21:19:27
技術ブログ	Developers.IO	[アップデート] NAT ゲートウェイに複数の IP アドレスを関連付け出来るようになりました	https://dev.classmethod.jp/articles/nat-gateways-capacity-concurrent-connections-unique-destination/	追加	2023-02-01 21:40:14
海外TECH	DEV Community	Autocomplete and Artificial Intelligence in your Terminal	https://dev.to/this-is-learning/autocomplete-and-artificial-intelligence-in-your-terminal-27fc	Autocomplete and Artificial Intelligence in your TerminalI get asked on every single video what is this autocomplete I ve got on my terminal and the answer is drum rolls fig io Actually it s much more than a simple autocomplete even if to be honest it s what I use of the time If you want to see a showcase of some of the major features as usual I recorded a video and you can find it on YouTube Still here If you re not a video guy feel free to read the article instead AutocompleteLet s give a closer look at autocomplete What you could expect from an autocomplete is to suggest you the next command while typing it Or for example getting the list of all the files in the current directory Fig does much much more When you start typing a command for example git checkout you will see fig suggesting all the possible flags and options you can use for example force or b Enough Not yet You can also see on the recommendations all the available branches you can pass as argument to the command I mean it s cool on an image but you should really have a look at the video to see it in action You will be surprised to notice that as soon as you start typing git you will see in the autocomplete some weird commands like cma or lgo What are those Well they are the aliases I defined in my dotfiles and fig is able to read them and suggest them to me Artificial IntelligenceThe coolest feature right after autocomplete is…well the name is self explanatory…artificial intelligence We re in AI is everywhere including our terminals With fig you can start typing fig ai to get some help To begin with let s start with a simple fig ai h to get the help English gt Bash translationUsage fig ai INPUT Arguments INPUT Options h help Print helpIt s all there on the first line it translates English to Bash Just write in plain english what you want to do and fig will translate it to a bash command for you Then you can either use it edit it or ask the ai to generate a new command Again I think it doesn t give it justice just written as a blog post you should really really watch the video or even better try it yourself Custom scriptsIn a concept similar to alias you can define some custom scripts and give them a name When you type fig run in your terminal you will get a list of all the scripts you defined There s also a script store where you can find some scripts other people created and use them directly in your terminal PluginsSimilar to the scripts and the script store you can find plugins aaaand a plugin store With plugins you can even further enhance your terminal experience DotfilesFig helps you manage aliases variables paths and more all in one place As you can see in the video I m not really using this feature but I think I should It s one of those nice to have that you can easily live without but once you discover them you start thinking why you haven t started using them earlier Open SourceDid I already mention the autocomplete is Open Source You can contribute on GitHub Plugins are open source too and you can add yours directly on the repo Actually feel free to go on the withfig page and have a look at all the repos there s a lot to discover ClosingAnd that s it It wasn t a paid sponsorship but I genuinely enjoy using fig s autocomplete every day and since you asked many times I though it was cool to make an entire piece of content about it Do you also use fig and its other features Let me know in the comments Thanks for reading this article I hope you found it interesting I recently launched my Discord server to talk about Open Source and Web Development feel free to join Do you like my content You might consider subscribing to my YouTube channel It means a lot to me ️You can find it here Feel free to follow me to get notified when new articles are out Leonardo MontiniFollow I talk about Open Source GitHub and Web Development I also run a YouTube channel called DevLeonardo see you there	2023-02-01 21:08:36
海外TECH	DEV Community	Prompt-driven search with LLMs	https://dev.to/neuml/prompt-driven-search-with-llms-4d07	Prompt driven search with LLMsThis article is part of a tutorial series on txtai an AI powered semantic search platform txtai executes machine learning workflows to transform data and build AI powered semantic search applications This article revisits the Extractor pipeline which has been covered in a number of previous notebooks This pipeline is a combination of a similarity instance embeddings or similarity pipeline to build a question context and a model that answers questions The Extractor pipeline recently underwent a number of major upgrades to support the following Ability to run embeddings searches Given that content is supported text can be retrieved from the embeddings instance In addition to extractive qa support text generation models sequence to sequence models and custom pipelinesThese changes enable embeddings guided and prompt driven search with Large Language Models LLMs Install dependenciesInstall txtai and all dependencies Install txtaipip install txtai datasets Create Embeddings and Extractor instancesAn Embeddings instance defines methods to represent text as vectors and build vector indexes for search The Extractor pipeline is a combination of a similarity instance embeddings or similarity pipeline to build a question context and a model that answers questions The model can be a prompt driven large language model LLM an extractive question answering model or a custom pipeline Let s run a basic example from txtai embeddings import Embeddingsfrom txtai pipeline import Extractor Create embeddings model with content supportembeddings Embeddings path sentence transformers all MiniLM L v content True Create extractor instanceextractor Extractor embeddings google flan t base data Giants hit HRs to down Dodgers Giants Dodgers final Dodgers drop Game against the Giants Blue Jays beat Red Sox final score Red Sox lost to the Blue Jays Blue Jays at Red Sox is over Score Phillies win over the Braves Phillies Braves final Final Braves lose to the Phillies in the series opener Lightning goaltender pulled lose to Flyers Flyers Lightning final Flyers win def prompt question return f Answer the following question using the context below Question question Context questions What team won the game What was score execute lambda query extractor question query prompt question False for question in questions data for query in Red Sox Blue Jays Phillies Braves Dodgers Giants Flyers Lightning print query for answer in execute query print answer print Red Sox Blue Jays What team won the game Blue Jays What was score Phillies Braves What team won the game Phillies What was score Dodgers Giants What team won the game Giants What was score Flyers Lightning What team won the game Flyers What was score This code runs a series of questions First it runs an embeddings filtering query to find the most relevant text For example Red Sox Blue Jays finds text related to those teams Then What team won the game and What was the score are asked This logic is the same logic found in Notebook Extractive QA with txtai but uses prompt based QA vs extractive QA Embeddings guided and Prompt driven SearchNow for the fun stuff Let s build an embeddings index for the ag news dataset a set of news stories from the mid s Then we ll use prompts to ask questions with embeddings results as the context from datasets import load datasetdataset load dataset ag news split train List of all text elementstexts dataset text Create an embeddings index over the datasetembeddings Embeddings path sentence transformers all MiniLM L v content True embeddings index x text None for x text in enumerate texts Create extractor instanceextractor Extractor embeddings google flan t large def prompt question return f Answer the following question using only the context below Say no answer when the question can t be answered Question question Context def search query question None Default question to query if empty if not question question query return extractor answer query prompt question False question Who won the presidential election answer search question print question answer nquestion Who did the candidate beat print nquestion search f question answer nquestion Who won the presidential election George W BushWho did the candidate beat John F KerryAnd there are the answers Let s unpack how this works The first thing the Extractor pipeline does is run an embeddings search to find the most relevant text within the index A context string is then built using those search results After that a prompt is generated run and the answer printed Let s see what a full prompt looks like text prompt question text n n join x text for x in embeddings search question print text Answer the following question using only the context below Say no answer when the question can t be answered Question Who won the presidential election Context Right and left click politics The presidential race ended last week in a stunning defeat for Massachusetts Senator John F Kerry as incumbent President George W Bush cruised to an easy victory Presidential Endorsements AP AP Newspaper endorsements in the presidential campaign between President Bush a Republican and Sen John Kerry a Democrat Presidential Campaign to Nov Reuters Reuters The following diary of events leading up to the presidential election on Nov The prompt has the information needed to determine the answers to the questions Additional examplesBefore moving on a couple more example questions question Who won the World Series in answer search question print question answer nquestion Who did they beat print nquestion search f question answer nquestion Who won the World Series in BostonWho did they beat St Louissearch Tell me something interesting herrings communicate by fartingWhhaaaattt Is this a model hallucination Let s run an embeddings query and see if that text is in the results answer herrings communicate by farting for x in embeddings search Tell me something interesting if answer in x text start x text find answer print x text start start len answer herrings communicate by fartingSure enough it is It appears that the FLAN T model has a bit of an immature sense of humor External API IntegrationIn addition to support for Hugging Face models the Extractor pipeline also supports custom question answer models This could be a call to the OpenAI API GPT Cohere API Hugging Face API or using langchain to manage that All that is needed is a Callable object or a function Let s see an example that uses the Hugging Face API to answer questions We ll use the original sports dataset to demonstrate import requestsdata Giants hit HRs to down Dodgers Giants Dodgers final Dodgers drop Game against the Giants Blue Jays beat Red Sox final score Red Sox lost to the Blue Jays Blue Jays at Red Sox is over Score Phillies win over the Braves Phillies Braves final Final Braves lose to the Phillies in the series opener Lightning goaltender pulled lose to Flyers Flyers Lightning final Flyers win def prompt question return f Answer the following question using the context below Question question Context Submits a series of prompts to the Hugging Face API This call can easily be switched to use the OpenAI API GPT Cohere API or a library like langchain def api prompts response requests post json inputs prompts return x generated text for x in response json Create embeddings model with content supportembeddings Embeddings path sentence transformers all MiniLM L v content True Create extractor instance submit prompts to the Hugging Face inference APIextractor Extractor embeddings api questions What team won the game What was score execute lambda query extractor question query prompt question False for question in questions data for query in Red Sox Blue Jays Phillies Braves Dodgers Giants Flyers Lightning print query for answer in execute query print answer print Red Sox Blue Jays What team won the game Blue Jays What was score Phillies Braves What team won the game Phillies What was score Dodgers Giants What team won the game Giants What was score Flyers Lightning What team won the game Flyers What was score Everything matches with first example above in Create Embeddings and Extractor instances except the prompts are run as an external API call The Embeddings instance can also swap out the vectorization database and vector store components with external API services Check out the txtai documentation documentation for more information Wrapping upThis notebook covered how to run embeddings guided and prompt driven search with LLMs This functionality is a major step forward towards Generative Semantic Search for txtai More to come stay tuned	2023-02-01 21:07:17
Apple	AppleInsider - Frontpage News	Samsung Galaxy S23 vs iPhone 14 Pro - compared	https://appleinsider.com/articles/23/02/01/samsung-galaxy-s23-vs-iphone-14-pro---compared?utm_medium=rss	Samsung Galaxy S vs iPhone Pro comparedSamsung has released its answer to the iPhone Pro and other smartphones Here s how the Galaxy S compares against the iPhone Pro Galaxy S vs iPhone ProSamsung has officially introduced its new array of smartphones which includes the Galaxy S Galaxy S and Galaxy S Ultra a few months after Apple released its iPhone lineup Read more	2023-02-01 21:23:37
Apple	AppleInsider - Frontpage News	White House calls Apple and Google 'harmful' in bid to cut app store fees	https://appleinsider.com/articles/23/02/01/white-house-aims-to-cut-app-fees-calls-apple-and-google-harmful?utm_medium=rss	White House calls Apple and Google x harmful x in bid to cut app store feesThe National Telecommunications and Information Administration wants Apple and Google to be forced to have third party app stores saying that as is the model inflates prices and reduces innovation As Apple prepares to raise App Store prices outside the US the NTIA says that Apple and Google s business model is harmful to consumers and developers Following an investigation then NTIA says it has found that the current mobile app store model has provided a range of benefits to both app developers and users but has also created conditions of competition that are suboptimal Read more	2023-02-01 21:25:23
海外TECH	Engadget	Nintendo brings back discounted game vouchers for Switch Online subscribers	https://www.engadget.com/nintendo-switch-game-vouchers-212518285.html?src=rss	Nintendo brings back discounted game vouchers for Switch Online subscribersDon t worry if you missed out on Nintendo s bargain game vouchers from ーthey re back The company is once again offering a pair of vouchers for to Switch Online subscribers If you buy two eligible games this could save you on each Needless to say this could help you score a deal for a a blockbuster like The Legend of Zelda Tears of the Kingdom even when it s brand new There are conditions beyond the limited catalog You have to use the vouchers within a year so you can t save them for perpetuity You also can t hold more than eight at a time You do get My Nintendo Gold Points equivalent to five percent of what you pay though Nintendo doesn t say if or when the vouchers willThere s no secret behind the strategy for the vouchers Nintendo clearly hopes you ll not only join Switch Online but commit to buying multiple games where you might have otherwise bought just one Still it s difficult to ignore the value Even one set of vouchers can recoup the cost of Switch Online if you were already planning to buy games In theory you could quickly build a collection of major titles while saving a significant amount of money	2023-02-01 21:25:18
海外TECH	CodeProject Latest Articles	How to Install Home Assistant Container on Windows and Publish an MQTT Message	https://www.codeproject.com/Articles/5353463/How-to-Install-Home-Assistant-Container-on-Windows	How to Install Home Assistant Container on Windows and Publish an MQTT MessageIn this article I will show you how to install Home Assistant Container on Windows using Docker and Portainer get it working with Agent DVR and send an MQTT message from Agent DVR using CodeProject AI Server to detect a person	2023-02-01 21:15:00
ニュース	BBC News - Home	Russia planning invasion anniversary offensive - Ukraine	https://www.bbc.co.uk/news/world-europe-64492938?at_medium=RSS&at_campaign=KARANGA	russia	2023-02-01 21:43:26
ニュース	BBC News - Home	Rishi Sunak under pressure over what he knew about claims against Dominic Raab	https://www.bbc.co.uk/news/uk-politics-64482998?at_medium=RSS&at_campaign=KARANGA	aides	2023-02-01 21:10:51
ニュース	BBC News - Home	Nikki Haley poised to enter 2024 presidential race	https://www.bbc.co.uk/news/world-us-canada-64489485?at_medium=RSS&at_campaign=KARANGA	february	2023-02-01 21:08:45
ニュース	BBC News - Home	Man Utd 2-0 Nottingham Forest (5-0 on agg): Erik ten Hag's side to play Newcastle in Carabao Cup final	https://www.bbc.co.uk/sport/football/64395351?at_medium=RSS&at_campaign=KARANGA	Man Utd Nottingham Forest on agg Erik ten Hag x s side to play Newcastle in Carabao Cup finalManchester United beat Nottingham Forest in the Carabao Cup semi final to set up a Wembley final with Newcastle	2023-02-01 21:52:00
ニュース	BBC News - Home	Tom Brady retires 'for good' after 23 seasons in NFL	https://www.bbc.co.uk/sport/american-football/64487463?at_medium=RSS&at_campaign=KARANGA	brady	2023-02-01 21:16:14
ニュース	BBC News - Home	Celtic 3-0 Livingston: Taylor, Maeda & Kyogo score in first half	https://www.bbc.co.uk/sport/football/64395317?at_medium=RSS&at_campaign=KARANGA	livingston	2023-02-01 21:39:01
ニュース	BBC News - Home	Hearts 0-3 Rangers: Visitors surge to convincing win	https://www.bbc.co.uk/sport/football/64395319?at_medium=RSS&at_campaign=KARANGA	tynecastle	2023-02-01 21:43:42
ニュース	BBC News - Home	Parents take unpaid leave	https://www.bbc.co.uk/news/uk-england-bristol-64469851?at_medium=RSS&at_campaign=KARANGA	bristol	2023-02-01 21:24:22
ビジネス	東洋経済オンライン	丸川議員｢愚か者｣やじ反省に透ける自民党の計算 岸田政権下で冷遇される安倍元首相の秘蔵っ子 | 国内政治 | 東洋経済オンライン	https://toyokeizai.net/articles/-/649916?utm_source=rss&utm_medium=http&utm_campaign=link_back	丸川珠代	2023-02-02 06:40:00
ビジネス	東洋経済オンライン	宇多田ヒカルの名曲で露呈した台湾社会の一断面 ｢First Love｣を歌った台湾芸能界の大御所と社会のギャップ | 中国･台湾 | 東洋経済オンライン	https://toyokeizai.net/articles/-/649826?utm_source=rss&utm_medium=http&utm_campaign=link_back	firstlove	2023-02-02 06:20:00