投稿時間:2021-08-21 05:24:17 RSSフィード2021-08-21 05:00 分まとめ(29件)

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AWS	AWS DevOps Blog	Deploying Alexa Skills with the AWS CDK	https://aws.amazon.com/blogs/devops/deploying-alexa-skills-with-aws-cdk/	Deploying Alexa Skills with the AWS CDKYou can and should strive for Infrastructure as Code IaC and CI CD in every project including your Alexa Skills Come learn how to use the AWS CDK to define your Alexa Skills as code and deploy them with a single CLI command or as part of a CI CD workflow	2021-08-20 19:02:43
AWS	AWS Messaging and Targeting Blog	Orchestrating and Monitoring Multichannel Messaging with Amazon Pinpoint	https://aws.amazon.com/blogs/messaging-and-targeting/orchestrating-and-monitoring-multichannel-messaging-with-amazon-pinpoint/	Orchestrating and Monitoring Multichannel Messaging with Amazon PinpointThe union of marketing and technology MarTech has contributed to making communications and customers interactions more dynamic and personalized In a multichannel environment with increasingly connected customers it is essential for a MarTech system to orchestrate a digital marketing strategy using customers preferred channels in addition to monitoring their effectiveness during these engagements Companies in …	2021-08-20 19:38:26
python	Pythonタグが付けられた新着投稿 - Qiita	PC超絶初心者が3か月プログラミング学んでみた	https://qiita.com/tencyou8808/items/0c488cbb70a9964e3915	PC初心者でも、これくらい出来るようになります今回の環境oswindowspythonJupyterNotebook今回やった事過去か月の実データのデータ成形重回帰分析を使った売数の予測今記事の主な内容今回、一番時間を割いた事は実際のデータ私が働いている店の売上データを使いましたを分析に使えるDataFrameに直すところです。	2021-08-21 04:39:31
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	【swift】iPhoneを使っているかどうかを検知する方法を教えてください	https://teratail.com/questions/355353?rss=all	【swift】iPhoneを使っているかどうかを検知する方法を教えてください前提・実現したいこと初めましてswiftUIでアプリ作成を今年度から少し始めたばかりの者です「iPhoneを使っているかどうか」を検知したいのですが、方法がありましたら教えていただけませんか・ある数時間の間にiPhoneを使ったかどうか・そのアプリがバックグラウンド状態で検知したいです。	2021-08-21 04:54:12
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	[初心者プロゲート]オブジェクトを要素に持つ配列について質問です。	https://teratail.com/questions/355352?rss=all	プロゲートで「オブジェクトを要素に持つ配列」という講座で以下のように習いました。	2021-08-21 04:39:01
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	wordpress5.8+php7.4で「お使いのサーバーの PHP では WordPress に必要な MySQL 拡張を利用できないようです。」と出力される	https://teratail.com/questions/355351?rss=all	apachemariadbnbspphpnbsp	2021-08-21 04:29:21
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Xcodeについて Apple	https://teratail.com/questions/355350?rss=all	apple	2021-08-21 04:17:10
海外TECH	DEV Community	RoadMap to dive into the world of Machine Learning	https://dev.to/saxenamansi/roadmap-to-dive-into-the-world-of-machine-learning-5179	RoadMap to dive into the world of Machine LearningIf you ve been reading about the amazing advancements in the world of Artificial Intelligence and Machine Learning but feel overwhelmed by its complexity this post is just for you After reading this blog you should have a clear understanding of how to embark on this journey of learning Machine Learning the right way so stick with me till the end Pre requisitesFirst things first what are the pre requisites of learning Machine Learning Just knowing the programming languages are not enough you must know the mathematics behind each algorithm too The important topics one must familiarize themselves with are Linear Algebra CalculusStatisticsIf you do not have a mathematical background Khan Academy is a good place to get started on the basics This Coursera Specialization Mathematics for Machine Learning is also a good resource if you can devote long hours for MOOCs Other resources are mentioned in these links below For Linear AlgebraFor StatisticsFor CalculusIf you are unfamiliar with Calculus I would recommend you to go through one of the books given in the link above and understand the basics of differentiation and integration as it is essential to the path to becoming a Machine Learning expert Coding fundamentalsOnce you have gotten confident with your math shift your focus to the coding part Many languages are used for writing Machine Learning programs like Python R Java and so on However python is the most recommended because of its several libraries and frameworks that have simplified the task of writing complex code Another reason I would recommend Python is because there are far more Machine Learning tutorials written in python than there are in R Thus it is easier for a python programmer to get help from the data science community than an R programmer However R is also known for its various data visualization libraries Thus there is no harm in learning both languages and utilizing their best features You can always learn one and move to the next For a beginner I would recommend python There are several resources to learn basic python but my favorite one is this Coursera specialization Python for Everybody by Charles Russell Severance of University of Michigan If this does not suit you you may try other resources given in this linkAnd voila you finally have all the pre requites you need to get started on your journey into the world of Machine Learning Taking the first stepThe first step is to complete these two renowned courses One will teach you about the Mathematics behind each Machine Learning algorithm by none other than the great Andrew NG and the other one will focus on the programming part You may choose to do them simultaneously Take your time with them as this will lay the foundations for this field Machine Learning by Andrew NG Stanford University You do not have to buy the course you may audit it too Just focus on watching all the videos in this course There is also a YouTube playlist with all the videos in this course which I will link here If you really are a ML nerd you ll be hooked on this course PS if you do not know who Andrew NG is google him RIGHT NOW you won t regret it The second course is Python for Data Science and Machine Learning Bootcamp by Jose Portilla This course can be a little heavy as it is introduces you to all the major programming concepts used in Machine Learning So take your time with it and keep trying out the codes and functions taught in the course yourself just listening to videos will not help much until you get your hands dirty Getting your hands dirtyWhile coding if you get stuck with an error and you are unable to solve it search the error on stack overflow There would definitely be someone who has been in your shoes before and has suffered through the error that you are facing now Read through the answers and solutions that others have suggested to solve the error On the off chance that the error you are facing is not encountered by anyone else post your own query Don t be shy you d be surprised at how beginner friendly and helpful the data science community is After all everyone was once a beginner Applying what you learnt Starting with some baby projectsAfter completing these courses you can safely say that you now have a good understanding of the classical algorithms You can now start working on some baby projects Find datasets on Kaggle that interest you and put your newly learnt python skills to use You may also try going through the code that other developers have written However some of it might be too complex so do not be too hard on yourself if you are unable to understand all of it With each dataset that you work with you will learn new functions and concepts of data cleaning data augmentation preprocessing data encoding and so on The codes of some of the baby projects that I had made are on my GitHub They should be easy to follow not too complex HR Analytics Employee Retention using Logistic RegressionBreast Cancer Classification using Decision TreesCleaning Student Profile DataPreprocessing and Cleaning Stroke DataRecognizing Hand Written Digits using PCA and SVM techniquesClustering Credit Card Data using Gaussian Mixtures and PCAClustering Geo Locations using K Means clusteringUsing Numpy and Matplotlib for Image ProcessingData Visualization of Australian WildfiresComparing the classification algorithms for Mushroom ClassificationComparing the classification algorithms for Credit Card FraudsData Visualization and Comparing the classification algorithms for Household Electricity ConsumptionData Visualization and Comparing the classification algorithms for grades of Maths and Portuguese class studentsI would urge you to first try them yourselves and then check my codes for reference Whenever you come across a new function read the documentation and check what it does Make sure you understand all of it And that s it With this you should now have a concrete understanding of the Machine Learning algorithms and how to use them You should also be fairly acquainted with some data cleaning data preprocessing and data visualization techniques Deep Learning the path after Machine LearningIf you have found the journey up till now interesting you may dive into the Deep Learning as well The best way to do so is by getting started with this in depth Deep Learning specialization by Andrew NG It will require some dedication as it consists of courses but it is very thorough and you will not need any material apart from this Your path from here to becoming a Data ScientistWhen you start on this path of Data Science you must be aware that in this domain learning never stops Once you complete the above specialization you can continue on this path by Participating in Kaggle competitions Reading the best research papers in the topics from your interest Doing more MOOCs from Coursera I would recommend the courses from the DeepLearning ai foundation Start working on your own projects Try developing them into products for common users to use You may also try publishing it in a reputed journal Share your knowledge with the world help other beginners on stack overflow and write blogs Push your work to GitHub for others to learn from Do like this post if it helped you If you have any other suggestions or recommendations let me know in the comments below Happy Learning lt	2021-08-20 19:23:11
海外TECH	DEV Community	Running Containerized Microservices on AWS | AWS White Paper Summary	https://dev.to/awsmenacommunity/running-containerized-microservices-on-aws-aws-white-paper-summary-54o8	Running Containerized Microservices on AWS AWS White Paper SummaryThis whitepaper is intended for architects and developers who want to run containerized applications at scale in production on Amazon Web Services AWS This document provides guidance for application lifecycle management security and architectural software design patterns for container based applications on AWS It also discusses architectural best practices for adoption of containers on AWS and how traditional software design patterns evolve in the context of containers It leverages Martin Fowler s principles of microservices and map them to the twelve factor app pattern and real life considerations After reading this paper you will have a starting point for building microservices using best practices and software design patterns Microservices are an architectural and organizational approach to software development in which software is composed of small independent services that communicate to each other There are different ways microservices can communicate but the two commonly used protocols are HTTP request response over well defined APIs and lightweight asynchronous messaging Microservices architectures make applications easier to scale and faster to develop This enables innovation and accelerates time to market for new features Containers also provide isolation and packaging for software and help you achieve more deployment velocity and resource density As proposed by Martin Fowler the characteristics of a microservices architecture include the following Componentization via servicesOrganized around business capabilitiesProducts not projectsSmart endpoints and dumb pipesDecentralized governanceDecentralized data managementInfrastructure automationDesign for failureEvolutionary designThe twelve factors are a set of best practices for building modern applications that are optimized for cloud computing The twelve factors cover four key areas deployment scale portability and architecture Codebase One codebase tracked in revision control many deploysDependencies Explicitly declare and isolate dependenciesConfig Store configurations in the environmentBacking services Treat backing services as attached resourcesBuild release run Strictly separate build and run stagesProcesses Execute the app as one or more stateless processesPort binding Export services via port bindingConcurrency Scale out via the process modelDisposability Maximize robustness with fast startup and graceful shutdownDev prod parity Keep development staging and production as similar as possibleLogs Treat logs as event streamsAdmin processes Run admin management tasks as one offprocesses Componentization Via ServicesIn a microservices architecture software is composed of small independent services that communicate over well defined APIs An analogy can be drawn to the Walkman portable audio cassette players that were popular in the s batteries bring power audio tapes are the medium headphones deliver output while the main tape player takes input through key presses Using them together plays music Similarly microservices need to be decoupled and each should focus on one functionality Additionally a microservices architecture allows for replacement or upgrade Using the Walkman analogy if the headphones are worn out you can replace them without replacing the tape player Through modularization microservices offer developers the freedom to design each feature as a black box That is microservices hide the details of their complexity from other components Any communication between services happens by using well defined APIs to prevent implicit and hidden dependencies Container images allow for modularity in services They are constructed by building functionality onto a base image Developers operations teams and IT leaders should agree on base images that have the security and tooling profile that they want These images can then be shared throughout the organization as the initial building block Replacing or upgrading these base images is as simple as updating the FROM field in a Dockerfile and rebuilding usually through a Continuous Integration Continuous Delivery CI CD pipeline Here are the key factors from the twelve factor app pattern methodology that play a role in componentization Dependencies explicitly declare and isolate dependencies Dependencies are self contained within the container and not shared with other services Disposability maximize robustness with fast startup and graceful shutdown Disposability is leveraged and satisfied by containers that are easily pulled from a repository and discarded when they stop running Concurrency scale out via the process model Concurrency consists of tasks or pods made of containers working together that can be auto scaled in a memory and CPU efficient manner Organized Around Business CapabilitiesBefore microservices system architecture would be organized around technological capabilities such as user interface database and server side logic In a microservices based approach as a best practice each development team owns the lifecycle of its service all the way to the customer For example a recommendations team might own development deployment production support and collection of customer feedback Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations Conway s Law When architecture and capabilities are organized around atomic business functions dependencies between components are loosely coupled As long as there is a communication contract between services and teams each team can run at its own speed With this approach the stack can be polyglot meaning that developers are free to use the programming languages that are optimal for their component For example the user interface can be written in JavaScript or HTML the backend in Java and data processing can be done in Python The following are key factors from the twelve factor app pattern methodology that play a role in organizing around capabilities Codebase one codebase tracked in revision control many deploys Each microservice owns its own codebase in a separate repository and throughout the lifecycle of the code change Build release run strictly separate build and run stages Each microservice has its own deployment pipeline and deployment frequency This allows the development teams to run microservices at varying speeds so they can be responsive to customer needs Processes execute the app as one or more stateless processes Each microservice does one thing and does that one thing really well The microservice is designed to solve the problem at hand in the best possible manner Admin processes run admin management tasks as one offprocesses Each microservice has its own administrative or management tasks so that it functions as designed To achieve a microservices architecture that is organized around business capabilities use popular microservices design patterns A design pattern is a general reusable solution to a commonly occurring problem within a giving context Popular miscroservice design patterns include Aggregator Pattern A basic service which invokes other services to gather the required information or achieve the required functionality This is beneficial when you need an output by combining data from multiple microservices API Gateway Design Pattern API Gateway also acts as the entry point for all the microservices and creates fine grained APIs for different types of clients It can fan out the same request to multiple microservices and similarly aggregate the results from multiple microservices Chained or Chain of Responsibility Pattern Chained or Chain of Responsibility Design Patterns produces a single output which is a combination of multiple chained outputs object Asynchronous Messaging Design Pattern In this type of microservices design pattern all the services can communicate with each other but they do not have to communicate with each other sequentially and they usually communicate asynchronously Database or Shared Data Pattern This design pattern will enable you to use a database per service and a shared database per service to solve various problems These problems can include duplication of data and inconsistency different services have different kinds of storage requirements few business transactions can query the data and with multiple services and de normalization of data Event Sourcing Design Pattern This design pattern helps you to create events according to change of your application state Command Query Responsibility Segregator CQRS Design Pattern This design pattern enables you to divide the command and query Using the common CQRS pattern where the command part will handle all the requests related to CREATE UPDATE DELETE while the query part will take care of the materialized views Circuit Breaker Pattern This design pattern enables you to stop the process of the request and response when the service is not working For example when you need to redirect the request to a different service after certain number of failed request intents Decomposition Design Pattern This design pattern enables you to decompose an application based on business capability or on based on the sub domains Products Not ProjectsCompanies that have mature applications with successful software adoption and who want to maintain and expand their user base will likely be more successful if they focus on the experience for their customers and end users To stay healthy simplify operations and increase efficiency your engineering organization should treat software components as products that can be iteratively improved and that are constantly evolving When software architecture is broken into small microservices it becomes possible for each microservice to be an individual product For internal microservices the end user of the product is another team or service For an external microservice the end user is the customer The core benefit of treating software as a product is improved end user experience When your organization treats its software as an always improving product rather than a one offproject it will produce code that is better architected for future work The following are key factors from the twelve factor app pattern methodology that play a role in adopting a product mindset for delivering software Build release run Engineers adopt a devops culture that allows them to optimize all three stages Config Engineers build better configuration management for software due to their involvement with how that software is used by the customer Dev prod parity Software treated as a product can be iteratively developed in smaller pieces that take less time to complete and deploy than long running projects which enables development and production to be closer in parity Smart Endpoints and Dumb PipesThere are two primary forms of communication between services Request Response One service explicitly invokes another service by making a request to either store data in it or retrieve data from it For example when a new user creates an account the user service makes a request to the billing service to pass offthe billing address from the user s profile so that that billing service can store it Publish Subscribe Event based architecture where one service implicitly invokes another service that was watching for an event For example when a new user creates an account the user service publishes this new user signup event and the email service that was watching for it is triggered to email the user asking them to verify their email The core benefit of building smart endpoints and dumb pipes is the ability to decentralize the architecture particularly when it comes to how endpoints are maintained updated and extended One goal of microservices is to enable parallel work on different edges of the architecture that will not conflict with each other Building dumb pipes enables each microservice to encapsulate its own logic for formatting its outgoing responses or supplementing its incoming requests The following are the key factors from the twelve factor app pattern methodology that play a role in building smart endpoints and dumb pipes Port Binding Services bind to a port to watch for incoming requests and send requests to the port of another service The pipe in between is just a dumb network protocol such as HTTP Backing services Dumb pipes allow a background microservice to be attached to another microservice in the same way that you attach a database Concurrency A properly designed communication pipeline between microservices allows multiple microservices to work concurrently For example several observer microservices may respond and begin work in parallel in response to a single event produced by another microservice Decentralized GovernanceDecentralized governance is an approach that works well alongside microservices to enable engineering organizations to tackle this challenge Traffic lights are a great example of decentralized governance City traffic lights may be timed individually or in small groups or they may react to sensors in the pavement Decentralized governance helps remove potential bottlenecks that would prevent engineers from being able to develop the best code to solve business problems Decentralized governance means that each team can use its expertise to choose the best tools to solve their specific problem Forcing all teams to use the same database or the same runtime language isn t reasonable because the problems they re solving aren t uniform The following are the key factors from the twelve factor app pattern methodology that play a role in enabling decentralized governance Dependencies Decentralized governance allows teams to choose their own dependencies so dependency isolation is critical to make this work properly Build release run Decentralized governance should allow teams with different build processes to use their own toolchains yet should allow releasing and running the code to be seamless even with differing underlying build tools Backing services If each consumed resource is treated as if it was a third party service then decentralized governance allows the microservice resources to be refactored or developed in different ways as long as they obey an external contract for communication with other services Decentralized Data ManagementAll data bound communication should be enabled via services that encompass the data As a result each service team chooses the most optimal data store type and schema for their application Decentralized data management enhances application design by allowing the best data store for the job to be used The following are the key factors from the twelve factor app pattern methodology that play a role in organizing around capabilities Disposability maximize robustness with fast startup and graceful shutdown The services should be robust and not dependent on externalities This principle further allows for the services to run in a limited capacity if one or more components fail Backing services treat backing services as attached resources A backing service is any service that the app consumes over the network such as data stores messaging systems etc Typically backing services are managed by operations The app should make no distinction between a local and an external service Admin processes run admin management tasks as one offprocesses The processes required to do the app s regular business for example running database migrations Admin processes should be run in a similar manner irrespective of environments To achieve a microservices architecture with decoupled data management the following software design patterns can be used Controller Helps direct the request to the appropriate data store using the appropriate mechanism Proxy Helps provide a surrogate or placeholder for another object to control access to it Visitor Helps represent an operation to be performed on the elements of an object structure Interpreter Helps map a service to data store semantics Observer Helps define a one to many dependency between objects so that when one object changes state all of its dependents are notified and updated automatically Decorator Helps attach additional responsibilities to an object dynamically Decorators provide a flexible alternative to sub classing for extending functionality Memento Helps capture and externalize an object s internal state so that the object can be returned to this state later Infrastructure AutomationThe following are the key factors from the twelve factor app pattern methodology that play a role in evolutionary design Codebase one codebase tracked in revision control many deploys Because the infrastructure can be described as code treat all code similarly and keep it in the service repository Config store configurations in the environment The environment should hold and share its ow specificities Build release run strictly separate build and run stages One environment for each purpose Disposability maximize robustness with fast startup and graceful shutdown This factor transcends the process layer and bleeds into such downstream layers as containers virtual machines and virtual private cloud Dev prod parity Keep development staging and production as similar as possible Ultimately the goal is to enable developers to push code updates and have the updated application sent to multiple environments in minutes There are many ways to successfully deploy in phases including the blue green and canary methods With the blue green deployment two environments live side by side with one of them running a newer version of the application Traffic is sent to the older version until a switch happens that routes all traffic to the new environment In this case we use a switch of target groups behind a load balancer in order to redirect traffic from the old to the new resources Another way to achieve this is to use services fronted by two load balancers and operate the switch at the DNS level Design for FailureEverything fails all the timeHere are the key factors from the twelve factor app pattern methodology that play a role in designing for failure Disposability maximize robustness with fast startup and graceful shutdown Produce lean container images and strive for processes that can start and stop in a matter of seconds Logs treat logs as event streams If part of a system fails troubleshooting is necessary Ensure that material for forensics exists Dev prod parity Keep development staging and production as similar as possible Modern container management services allow developers to retrieve near real time event driven updates on the state of containers Docker supports multiple logging drivers Container monitoring solutions use metric capture analytics transaction tracing and visualization Container monitoring covers basic metrics like memory utilization CPU usage CPU limit and memory limit Container monitoring also offers the real time streaming logs tracing and observability that containers need Evolutionary DesignThe following are the key factors from the twelve factor app pattern methodology that play a role in evolutionary design •Codebase one codebase tracked in revision control many deploys Helps evolve features faster since new feedback can be quickly incorporated •Dependencies explicitly declare and isolate dependencies Enables quick iterations of the design since features are tightly coupled with externalities •Configuration store configurations in the environment Everything that is likely to vary between deploys staging production developer environments etc Config varies substantially across deploys code does not With configurations stored outside code the design can evolve irrespective of the environment •Build release run strictly separate build and run stages Help roll out new features using various deployment techniques Each release has a specific ID and can be used to gain design efficiency and user feedback The following software design patterns can be used to achieve an evolutionary design •Sidecar extends and enhances the main service •Ambassador creates helper services that send network requests on behalf of a consumer service or application •Chain provides a defined order of starting and stopping containers •Proxy provides a surrogate or placeholder for another object to control access to it •Strategy defines a family of algorithms encapsulates each one and makes them interchangeable Strategy lets the algorithm vary independently from the clients that use it •Iterator provides a way to access the elements of an aggregate object sequentially without exposing its underlying representation •Service Mesh is a dedicated infrastructure layer for facilitating service to service communications between microservices using a proxy Deployment strategies such as a Canary release provide added agility to evolve design based on user feedback Canary release is a technique that s used to reduce the risk inherent in a new software version release In a canary release the new software is slowly rolled out to a small subset of users before it s rolled out to the entire infrastructure and made available to everybody In the diagram that follows a canary release can easily be implemented with containers using AWS primitives As a container announces its health via a health check API the canary directs more traffic to it The state of the canary and the execution is maintained using Amazon DynamoDB Amazon Route Amazon CloudWatch Amazon Elastic Container Service Amazon ECS and AWS Step Functions ConclusionMicroservices can be designed using the twelve factor app pattern methodology and software design patterns enable you to achieve this easily These software design patterns are well known If applied in the right context they can enable the design benefits of microservices AWS provides a wide range of primitives that can be used to enable containerized microservices References Original paper	2021-08-20 19:17:57
Apple	AppleInsider - Frontpage News	San Francisco doctor charged with possessing child pornography in iCloud	https://appleinsider.com/articles/21/08/20/san-francisco-doctor-charged-with-possessing-child-pornography-in-icloud?utm_medium=rss	San Francisco doctor charged with possessing child pornography in iCloudAmid controversy surrounding Apple s CSAM detection system a San Francisco Bay Area doctor has been charged with possessing child pornography in his Apple iCloud account according to federal authorities Credit AppleThe U S Department of Justice announced Thursday that Andrew Mollick had at least sexually exploitative images and videos of children stored in his iCloud account Mollick is an oncology specialist affiliated with several Bay Area medical facilitates as well as an associate professor at UCSF School of Medicine Read more	2021-08-20 19:40:51
海外TECH	Engadget	Peloton's Android app hints at long-rumored rowing machine	https://www.engadget.com/peloton-android-app-apk-rowing-machine-193223438.html?src=rss	Peloton x s Android app hints at long rumored rowing machineConducting an APK teardown of the latest version of the Peloton Android app toGoogle found evidence the company is preparing the software to support a rowing machine in the near future The outlet found various code snippets that mentioned a device codenamed quot Caesar quot and quot Mazu quot The latter is a reference to a Chinese sea goddess Like the company s stationary bike it appears the rowing machine will include a quot scenic rides quot feature that will showcase waterways from around the globe And if you want to just row that will be an option too Another set of snippets reference the four positions of a proper rowing technique quot This is the drive position of your stroke quot the app explains quot Sit tall on the rower with your arms straight and your back upright Your knees should be just above the ankles quot Digging deeper into the updated software to also found code suggesting the app will track metrics like your average and max stroke rates A rowing machine is something Peloton has been rumored to be working for a while now with a recent job listing mentioning the device We ve reached out to Pelton for confirmation but we ll note here what we say with all APK teardowns the fact there s code pointing to a new hardware release doesn t mean a company will follow through on that work or that a launch is imminent nbsp	2021-08-20 19:32:23
海外TECH	Engadget	'Halo Infinite' won't have campaign co-op or Forge modes at launch	https://www.engadget.com/halo-infinite-campaign-co-op-forge-release-date-343-industries-190153091.html?src=rss	x Halo Infinite x won x t have campaign co op or Forge modes at launchHalo Infinite is on track to hit Xbox consoles PC and Xbox Cloud Gaming sometime this holiday season but some key modes will be missing at the outset In a development update Industries said campaign co op and Forge won t be available at launch as the studio is focusing on the single player campaign and multiplayer modes quot Unfortunately as we focused the team for shutdown and really focused on a quality experience for launch we made the really tough decision to delay shipping campaign co op for launch quot Halo Infinite head of creative Joseph Staten said in the video quot We also made the tough call to delay shipping Forge past launch as well quot Industries will roll out the modes next year as part of its seasonal roadmap Right now the plan is to release campaign co op in season two around three months after the game debuts and Forge in season three approximately six months after launch Those plans may change though quot Our number one priority is making sure that whatever we ship whenever we ship it it meets the right quality bar across all platforms quot Staten said quot When we looked at these two experiences campaign co op and Forge we made the determination they re just not ready quot nbsp Campaign co op has long been a staple of the Halo series with up to four people being able to tackle the main campaign together In Forge players can create custom game modes with modified maps and unique rules nbsp The delays will likely come as a disappointment to fans who ve already had to wait longer than expected for the next game in the flagship Xbox franchise Halo Infinite wasn t ready in time for the Xbox Series X S launch last November As such Microsoft delayed the game until a year after it was initially supposed to arrive As for the specific Halo Infinite release date Staten said Industries plans to announce that soon Along with the single player campaign there s a free to play multiplayer mode You ll just have to remain patient a bit longer if you want to play through the campaign with your buddies	2021-08-20 19:02:05
海外科学	NYT > Science	Maker of Popular Covid Test Told Factory to Destroy Inventory	https://www.nytimes.com/2021/08/20/us/abbott-covid-tests.html	Maker of Popular Covid Test Told Factory to Destroy InventoryOne of the leading producers of rapid tests purged supplies and laid off workers as sales dwindled Weeks later the U S is facing a surge in infections with diminished capacity	2021-08-20 19:54:42
海外TECH	WIRED	Google Docs Scams Still Pose a Threat	https://www.wired.com/story/google-docs-scams-threat-phishing	protections	2021-08-20 19:35:12
海外TECH	WIRED	OnlyFans’ Explicit Content Ban Betrays Its Creators	https://www.wired.com/story/onlyfans-betrays-creators	OnlyFans Explicit Content Ban Betrays Its CreatorsThe adult fansite made its name off of personalized porn This week it announced that it would restrict “sexually explicit conduct starting in October	2021-08-20 19:25:42
ニュース	BBC News - Home	Joe Biden to Americans in Afghanistan: 'We will get you home'	https://www.bbc.co.uk/news/world-us-canada-58285923	afghanistan	2021-08-20 19:38:42
ニュース	BBC News - Home	'They will kill me': Desperate Afghans seek way out after Taliban takeover	https://www.bbc.co.uk/news/world-asia-58286372	taliban	2021-08-20 19:32:19
ビジネス	ダイヤモンド・オンライン - 新着記事	撮り鉄が深夜に外国人を罵倒の「江ノ電騒動」、近所もマナーの悪さに大迷惑 - from AERAdot.	https://diamond.jp/articles/-/278941	撮り鉄が深夜に外国人を罵倒の「江ノ電騒動」、近所もマナーの悪さに大迷惑fromAERAdot電車を前に、熱心にカメラを構える鉄道ファンのいわゆる「撮り鉄」。	2021-08-21 04:55:00
ビジネス	ダイヤモンド・オンライン - 新着記事	6～12歳の子どもの語彙力を伸ばすのに、水泳が役立つ!? - ヘルスデーニュース	https://diamond.jp/articles/-/279046	歳の小児を対象に、運動の種類と語彙習得との関連を検討した結果、有酸素運動との間に有意な関連が認められたとする研究結果が報告された。	2021-08-21 04:50:00
ビジネス	ダイヤモンド・オンライン - 新着記事	ゴルフ用の「ハーフパンツ」はどう選ぶ？【おすすめコーデ5選】 - 男のオフビジネス	https://diamond.jp/articles/-/278937	露出	2021-08-21 04:45:00
ビジネス	ダイヤモンド・オンライン - 新着記事	死ぬまでに絶対見たい世界の「城」と「宮殿」【地球の歩き方セレクト】 - 地球の歩き方ニュース＆レポート	https://diamond.jp/articles/-/278939	死ぬまでに絶対見たい世界の「城」と「宮殿」【地球の歩き方セレクト】地球の歩き方ニュースレポート海外旅行ガイドブックの決定版『地球の歩き方』から、今回紹介する記事は、美しいたたずまいや豪華絢爛な装飾で訪れる人の心を魅了する城と宮殿です。	2021-08-21 04:40:00
ビジネス	ダイヤモンド・オンライン - 新着記事	3つの問いでわかる「自分らしいキャリア」のかたち - 「日本版ジョブ型」時代のキャリア戦略	https://diamond.jp/articles/-/279790	つの問いでわかる「自分らしいキャリア」のかたち「日本版ジョブ型」時代のキャリア戦略日本企業が「ジョブ型」へ舵を切ることにより、キャリアの前提となるゲームのルールが変わりつつある。	2021-08-21 04:35:00
ビジネス	ダイヤモンド・オンライン - 新着記事	ひろゆきが児童養護施設にパソコンを配るワケ - 1％の努力	https://diamond.jp/articles/-/278678	児童養護施設	2021-08-21 04:30:00
ビジネス	ダイヤモンド・オンライン - 新着記事	「利益率29％」を 縁の下で支える 業務改善の超絶ビフォー・アフター - 売上最小化、利益最大化の法則	https://diamond.jp/articles/-/276374		2021-08-21 04:25:00
ビジネス	ダイヤモンド・オンライン - 新着記事	企業での対話を成功させる 2つの“異色な”アプローチ - 組織が変わる	https://diamond.jp/articles/-/276744	慢性疾患ってうちの会社のことすべて見抜かれている」「『他者と働く』が慢性疾患の現状認識ツールなら、『組織が変わる』は慢性疾患の寛解ツールだ」「言語化できないモヤモヤの正体が形になって現れる体験は衝撃でした」職場に活気がない、会議で発言が出てこない、職場がギスギスしている、仕事のミスが多い、忙しいのに数字が上がらない、病欠が増えている、離職者が多い……これらを「組織の慢性疾患」と呼び、セルフケアの方法を初めて紹介した宇田川氏。	2021-08-21 04:20:00
ビジネス	ダイヤモンド・オンライン - 新着記事	コロナ禍でもフェアが大反響！ 大手書店店長が語る「SNS時代」に客を呼ぶ方法 - 独学大全	https://diamond.jp/articles/-/279872	突破	2021-08-21 04:15:00
ビジネス	ダイヤモンド・オンライン - 新着記事	アメリカ・ファーストの歴史、ワンダラーブラウス事件から石油戦争まで！ - 経済は統計から学べ！	https://diamond.jp/articles/-/280102	貿易統計	2021-08-21 04:10:00
ビジネス	ダイヤモンド・オンライン - 新着記事	なぜ、ワークマンでは マネジャー以上の退職者が 実質ゼロになったのか？ - ワークマン式「しない経営」	https://diamond.jp/articles/-/277081		2021-08-21 04:05:00
ビジネス	東洋経済オンライン	｢人生100年時代｣に｢FIRE｣したがる人の問題点 若いとき｢無理にお金を貯める｣とどうなる？ | 新競馬好きエコノミストの市場深読み劇場 | 東洋経済オンライン	https://toyokeizai.net/articles/-/449570?utm_source=rss&utm_medium=http&utm_campaign=link_back	東京オリンピック	2021-08-21 04:30:00