投稿時間:2023-04-04 06:18:17 RSSフィード2023-04-04 06:00 分まとめ(25件)

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海外TECH	Ars Technica	Today’s best deals: Apple MacBook Air, Apple Watch, Mac mini, Amazon Kindle	https://arstechnica.com/?p=1928670	kindles	2023-04-03 20:01:51
海外TECH	MakeUseOf	How to Use Excel's CHOOSE Function to Select Data Based on Criteria	https://www.makeuseof.com/use-excel-choose-function/	How to Use Excel x s CHOOSE Function to Select Data Based on CriteriaDo you struggle with selecting data in Excel Learn how to use the CHOOSE function to quickly and easily select data based on specific criteria	2023-04-03 20:30:17
海外TECH	MakeUseOf	How to Recover Deleted Facebook Messages	https://www.makeuseof.com/how-to-recover-deleted-messages-on-facebook/	facebook	2023-04-03 20:05:17
海外TECH	DEV Community	The Top 5 Skills You Need to Future-Proof Your Career in 2023 and Beyond	https://dev.to/alvisonhunter/the-top-5-skills-you-need-to-future-proof-your-career-in-2023-and-beyond-4pim	The Top Skills You Need to Future Proof Your Career in and BeyondWith the job market evolving rapidly it s essential to stay ahead of the curve and acquire the skills that will make you stand out from the competition In this post we ll explore the top five skills you need to future proof your career in and beyond Digital literacy In today s digital world it s critical to have a good understanding of technology and its applications This includes not only basic computer skills but also proficiency in advanced technologies such as artificial intelligence and blockchain Creative thinking As automation continues to replace routine tasks creativity and innovation are becoming more valuable than ever The ability to come up with original ideas and solutions will set you apart from others in your field Emotional intelligence The importance of emotional intelligence cannot be overstated The ability to understand and manage your own emotions as well as those of others is crucial in today s fast paced diverse workplaces Adaptability Change is constant in the modern workforce and the ability to adapt quickly is a must have skill Those who can quickly pivot and adjust to new situations and challenges will be in high demand Data analysis Data is becoming increasingly important in decision making across all industries Being able to collect analyze and interpret data is essential for professionals in many roles These are just a few of the skills you need to future proof your career in and beyond By focusing on developing these skills you ll be better equipped to thrive in the changing job market and stand out from the competition Good luck with the next job interview on any of these fields folks Thanks for reading this article I hope you enjoyed it as much as I did writing it Until next time dear readers ️Your enjoyment of this article encourages me to write further Kindly share your valuable opinion by leaving a comment Bookmark this article for future reference If this article has truly helped you please share it	2023-04-03 20:50:33
海外TECH	DEV Community	A Beginner's Guide to Prompt Engineering with GitHub Copilot	https://dev.to/github/a-beginners-guide-to-prompt-engineering-with-github-copilot-3ibp	A Beginner x s Guide to Prompt Engineering with GitHub CopilotWhen I started using GitHub Copilot and other generative AI tools I felt frustrated because I wasn t receiving the expected results How were people feeling so successful with these tools and why weren t they doing what I wanted For example I would ask GitHub Copilot to solve a LeetCode problem for me The GitHub Copilot icon would spin to indicate that it s thinking and then I would receive an incongruent suggestion or no suggestion at all I was annoyed but it turns out I was using it wrong After more experimentation I improved my communication methods with GitHub Copilot by providing context examples and clear instructions in the form of comments and code Later on I learned that this practice is called prompt engineering In this blog post I ll discuss top tips to help you get the most out of GitHub Copilot First let s start with the basics for folks who are unfamiliar with GitHub Copilot or prompt engineering What is GitHub Copilot GitHub Copilot is an AI pair programmer developed by GitHub and GitHub Copilot is powered by OpenAI Codex a generative pre trained language model created by OpenAI that provides contextualized code suggestions based on context from comments and code To use it you can install the GitHub Copilot extension available to you in the following Integrated Development Environments IDEs Visual StudioVisual Studio CodeNeovimJetBrains IDEs IntelliJ PyCharm WebStorm etc Can GitHub Copilot code on its own At GitHub we use the terms AI pair programmer AI assistant and Copilot to since this tool cannot work without you the developer In fact AI systems can only perform the tasks that developers program them to perform and they do not possess free will or the ability to make decisions independently In this case GitHub Copilot leverages context from the code and comments you write to suggest code instantly With GitHub Copilot you can convert comments to code autofill repetitive code and show alternative suggestions How does GitHub Copilot work under the hood Under the hood GitHub Copilot draws context from comments and code instantly suggesting individual lines and whole functions OpenAI Codex a machine learning model that can translate natural language into code powers GitHub Copilot What is prompt engineering Prompt engineering is the practice of giving an AI model specific instructions to produce the results you want A prompt is a sequence of text or a line of code that can trigger a response from an AI model You can liken this concept to receiving a prompt for an essay You can receive a prompt to write an essay about a time you overcame a challenge or a prompt to write about a classic book such as the Great Gatsby As a result you give a response to the prompt based on what you ve learned A logic learning machine or LLM will behave similarly Here s another illustration of prompt engineering When I learned to code I participated in an activity where I gave a robot instructions on how to make a sandwich It was a fun silly activity that taught me that Computers can only do what you tell them to doYou need to be very specific with your instructionsThey re better at taking orders one step at a timeAlgorithms are just a series of instructionsFor example if I were to tell the robot to make a sandwich I need to tell it Open the bag of breadTake the first two slices of bread out of the bagLay the slices of bread side by side on the counterSpread peanut butter on one slice of bread with a butter knifeEt cetera et cetera et ceteraWithout those clear instructions the robot might do something silly like spread peanut butter on both slices of bread or it might not do anything at all The robot doesn t know what a sandwich is and it doesn t know how to make one It just knows how to follow instructions Similarly GitHub Copilot needs clear step by step instructions to generate the code that best helps you Let s discuss best practices for prompt engineering to give clear instructions to GitHub Copilot and generate your desired results Best Practices for Prompt Engineering with GitHub Copilot Provide high level context followed by more detailed instructionsThe best technique for me is providing high level context in a comment at the top of the file followed by more detailed instructions in the form of comments and code For example if I m building a to do application At the top I ll write a comment that says Build a to do application using Next js that allows user to add edit and delete to do items Then on the following lines I ll write a comment to create the to do list component and I ll let GitHub Copilot generate the component underneath the commentbutton component and I ll let GitHub Copilot generate the component underneath the commentinput component and I ll let GitHub Copilot generate the component underneath the commentadd function and I ll let GitHub Copilot generate the function underneath the commentedit function and I ll let GitHub Copilot generate the function underneath the commentdelete function and I ll let GitHub Copilot generate the function underneath the commentetcetra etcetera etcetera Here s an example of me using this technique to build a house with p js In the following GIF I write a comment at the top describing at a high level what I want p js to draw I want to draw a white house with a red roof a red door and a brown chimney Then I write a comment for each element of the house and I let GitHub Copilot generate the code for each element Provide specific detailsWhen you provide specific details GitHub Copilot will be able to generate more accurate code suggestions For example if you want GitHub Copilot to retrieve data from an API you need to tell it what type of data you want to retrieve how to process the data and what API endpoint you re hoping to hit Here s an example of a non specific comment prompt where GitHub Copilot will be less likely to generate a useful suggestion Get data from APIfunction getData code goes here In the example above GitHub Copilot didn t generate anything for me besides the name of the function and the opening and closing brackets Here s an example of a specific comment prompt where GitHub Copilot will be more likely to generate a useful suggestion Pass in user ids and retrieve user data from jsonplaceholder typicode com API then return it as a JSON objectasync function getUserData userId const response await fetch userId const data await response json return data Provide examplesIn addition to telling GitHub Copilot what you want it to do you can also show it what you want it to do with examples in your preferred coding style While GitHub Copilot is using an AI model that is already trained on a large amount of data providing examples to GitHub Copilot help it understand the context and constraints of a particular code snippet Showing AI models examples of what you want them to do is a common practice in machine learning Here are a few approaches engineers use to train AI models Zero shot learningOne shot learningFew shot learningI asked ChatGPT to explain the difference between these methods to me like I was years old and here s what it gave me According to ChatGPT here are the differences between these approaches Zero shot learningThis is like when you see a new toy you ve never seen before but you know what it is because it looks like other toys you ve seen For example if you ve seen many different kinds of stuffed animals you might be able to recognize a new one even if you ve never seen that exact one before Similarly a computer can learn to recognize new things by using what it knows about similar things to make educated guesses about the new thing One shot learningThis is like when you see a new toy for the first time and your mom or dad tells you what it s called and what it does After hearing about it just once you remember what it is and can recognize it the next time you see it A computer can learn to recognize new things in the same way by being shown just a few examples and learning from them Few shot learningFew shot learning is like learning to do something new by seeing only a few examples For example let s say you want to learn how to draw a cat but you ve only seen a few pictures of cats before With few shot learning you can still learn how to draw a cat even if you haven t seen many cats before It s like a magic power that helps you learn new things quickly even if you don t have a lot of examples to learn from Here s what happened when I showed GitHub Copilot examples vs when I didn t show it examples No example Create a list of the first prime numbersprimes for num in range if all num i for i in range num primes append num print primes In the code snippet above GitHub Copilot will accurately return the first numbers however it s inefficient because it will loop through all numbers between and We can get more efficient results by providing an specific example of what we want GitHub Copilot to do With example Create a list of the first prime numbers Example primes for num in range if all num i for i in range num primes append num if len primes breakprint primes In the above code snippet GitHub Copilot will return the first ten prime numbers and stop when it s found all My goal was to get accurate but fast results and GitHub Copilot successfully achieved that after I nudged it in the right direction Additional tips Iterate your promptsIf your initial prompt elicits the desired response delete the generated code suggestion edit your comment with more details and examples and try again It s a learning process for you and GitHub Copilot The more you use it the better you ll get at communicating with GitHub Copilot Keep a tab opened of relevant files in your IDECurrently GitHub Copilot does not have the ability to gain context for your entire codebase However it can read your current file and any files that are opened in your IDE I ve found it helpful to keep an open tab of relevant files that I want GitHub Copilot to reference For example if I m writing a function that uses a variable from another file I ll keep that file open in my IDE This will help GitHub Copilot provide more accurate suggestions Give your AI assistant an identityI received this advice from Leilah Simone a Developer Advocate at BitRise I ve yet to try this with GitHub Copilot but it was helpful advice It helps to control the type of response the user will receive In Leila s case she requests that ChatGPT behave as a senior iOS engineer She says It s helped her reduce syntax and linting issues Use predictable patternsAs we saw in the many examples above GitHub Copilot will follow patterns in your code AI enthusiast and Developer Content Creator YK aka CS Dojo shares how he uses this to his advantage YK aka CS Dojo ykdojo blackgirlbytes Hope it s not too late but here it is I ve found that it works best when I follow a predictable pattern and when I let it do its own thing instead of fighting it For example when I write print some variabIt already knows that I want to print that variable Then I…twitter com i web status … AM Mar Use consistent specific naming conventions for variables and functions that describe their purposeWhen declaring variables or functions use names specific to the variable s purpose This will help GitHub Copilot understand the context of the variable and generate more relevant suggestions For example instead of using a generic variable name like value use a more specific name like input string or output file GitHub Copilot will also use the naming conventions you use in your code For example if you use camelCase for variables GitHub Copilot will suggest camelCase variables If you use snake case for variables GitHub Copilot will suggest snake case variables Use good coding practicesWhile GitHub Copilot can be a powerful tool for generating code suggestions it s important to remember that it s not a replacement for your own programming skills and expertise AI models are only as good as the data they have been trained on Therefore it s important to use these tools as aids and not rely on them entirely I encourage every user of GitHub Copilot to Review codeRun unit tests integration tests and any other programatic forms of testing codeManually test code to ensure it s working as intendedAnd to use good coding practices because GitHub Copilot will follow your coding style and patterns as a guide for its suggestions Beyond your editorCurrently GitHub Copilot is an extension that is available in the most popular IDEs There s also GitHub Copilot Labs a separate experimental extension available with GitHub Copilot access Copilot Labs can help you translate debug test document and refactor code Additionally we recently launched Copilot X a suite of features that improve developer productivity outside of the IDE Copilot X includes Copilot for Docs saves developers from scouring reams of documentation Copilot for Pull Requests helps you write better PR descriptions and to help your team review and merge PRs faster Copilot Chat a ChatGPT like experience in your editor with GitHub Copilot chat Copilot for CLI helps you remember shell commands and flags to run commands in your terminal faster Copilot Voice write and edit code navigate the codebase and control Visual Studio Code with your voice Copilot X features products are currently in technical preview If you d like access to one of the features above sign up for the waitlist at Start practicing prompt engineering with GitHub CopilotThe best way to learn how to use GitHub Copilot optimally is to start using it You can sign up for access to GitHub Copilot here If you re a business leader and you d like to give your entire team access to GitHub Copilot sign up for GitHub Copilot for Business here Let s keep learning togetherThanks for reading this blog post I d love to hear from you I m still learning more about artificial intelligence GitHub Copilot and prompt engineering If you re a GitHub Copilot fan and have learned how to use it to improve your developer workflow share some of your tips in the comments below For similar content follow GitHub and me on DEV to Also check out other resources to learn more about prompt engineering How to get Codex to produce the code you wantPrompt Design from OpenAIPrompt Engineering Introduction to CodexPrompt Engineering Guide by Elvis Saravia	2023-04-03 20:19:57
海外TECH	DEV Community	How to use chat gpt as a developer?🚀	https://dev.to/rafikadir/how-to-use-chat-gpt-as-a-developer-gcd	How to use chat gpt as a developer ChatGPT is a powerful tool for developers looking to create more efficient and engaging chat interfaces With its natural language processing capabilities it can help developers create more intuitive chat experiences for their users By leveraging the power of AI ChatGPT can be used to generate conversation trees and dialogue flows that allow users to interact with the system naturally With its easy to use APIs developers can quickly and easily integrate them into their applications In this article we will discuss how developers can use ChatGPT as web developers or programmers to create better user experiences Explain why a piece of code isn t working Explain what a piece of code means Rewrite the code using the specified language Code an entire software program Generate regular expressions regex Add comments to your codebase Change the CSS of a line of code Change the HTML of a line of code In conclusion ChatGPT is an excellent tool for developers to create conversational agents chatbots and other natural language processing applications By leveraging the power of machine learning natural language processing and neural networks developers can build intelligent agents that can understand and respond to user queries When using ChatGPT as a developer it s crucial to have a clear understanding of the application s requirements the data to be used and the expected output Developers must also have a basic understanding of machine learning and natural language processing concepts to leverage ChatGPT s full potential While working with ChatGPT developers must also keep in mind the ethical and privacy concerns surrounding the use of AI and natural language processing technologies It s essential to ensure that the applications built with ChatGPT are fair transparent and ethical and that they protect user privacy Overall ChatGPT is a powerful tool that can help developers build intelligent conversational agents and natural language processing applications By understanding its capabilities and limitations developers can leverage ChatGPT s full potential to build innovative and useful applications that can enhance user experience and drive business value	2023-04-03 20:11:53
海外TECH	Engadget	ASUS' ROG Ally is yet another Steam Deck competitor	https://www.engadget.com/asus-rog-ally-is-yet-another-steam-deck-competitor-204535105.html?src=rss	ASUS x ROG Ally is yet another Steam Deck competitorASUS isn t going to let the likes of Ayaneo or Valve have the handheld gaming PC market to themselves After an April st announcement that prompted skepticism don t announce real products on April Fools Day folks ASUS has confirmed that it s building its own handheld the ROG Ally While the company is light on details it notes the system will run Windows and use a custom AMD Ryzen chip You can even plug in an external GPU As The Vergenotes YouTuber Dave D has learned that the ROG Ally has a inch touchscreen but it s a ratio p display with a Hz refresh rate versus the Steam Deck s panel that only manages p and Hz Despite this ASUS handheld is narrower thinner and slightly lighter than Valve s machine It s not clear how that screen will affect battery life The company hasn t shared pricing or release dates However you can sign up for an alert when pre orders begin at Best Buy nbsp Whether or not the ROG Ally does well largely depends on its price and performance relative to the Steam Deck starting at and higher end handhelds like the Ayaneo As ASUS early marketing suggests though there are potentially strong advantages Unlike the Steam Deck which is officially limited to running games in your Steam library and only some at that the Ally can theoretically run most any game its hardware can handle And while brands like Ayaneo and GPD are relatively small ASUS is a major name ーyou ll likely have an easier time finding the Ally This article originally appeared on Engadget at	2023-04-03 20:45:35
海外TECH	Engadget	Activision Blizzard settles DOJ lawsuit over eSports wage suppression	https://www.engadget.com/activision-blizzard-settles-doj-lawsuit-over-esports-wage-suppression-202452240.html?src=rss	Activision Blizzard settles DOJ lawsuit over eSports wage suppressionThe US Department of Justice has settled a lawsuit it filed Monday with Activision Blizzard over suppressed eSports wages according toReuters The case submitted in the US District Court for the District of Columbia focuses on a rule that required independently owned teams to effectively pay double if they passed a soft salary cap A federal judge will still need to approve the settlement The complaint the fruit of an investigation first reported in said that in Activision s Overwatch and Call of Duty leagues the “competitive balance tax was structured to penalize teams if their compensation exceeded a threshold set by Activision “While players in other professional sports leagues have agreed to salary restrictions as part of collective bargaining agreements the players in Activision s esports leagues are not members of a union and never negotiated or bargained for these rules the DOJ clarified in the filing The case states that Activision would fine teams one dollar for every dollar that exceeded the cap ーand redistribute the collected fees among all non offending teams For example the filing says that “if Activision set a Competitive Balance Tax threshold of million a team that spent million on player compensation in a season would pay a fine which would be distributed to the other teams Additionally the Antitrust Division filed a proposed consent decree that would bar Activision from imposing any further rules that would penalize a team for exceeding a set amount of compensation It would also require the company to certify that “it has ended all Competitive Balance Taxes in its professional esports leagues to implement revised antitrust compliance and whistleblower protection policies and to provide notice and an explanation of the final judgment to teams and players in its professional esports leagues nbsp According to the DOJ the Overwatch and Call of Duty leagues have generated millions of dollars Microsoft is trying to clear regulatory hurdles to move forward with its planned purchase of Activision Blizzard “Video games and esports are among the most popular and fastest growing forms of entertainment in the world today and professional esports playersーlike all workersーdeserve the benefits of competition for their services Activision s conduct prevented that from happening said Assistant Attorney General Jonathan Kanter from the DOJ s Antitrust Division “Today s lawsuit makes clear that the Antitrust Division remains committed to protecting workers across all types of industries from anticompetitive conduct This article originally appeared on Engadget at	2023-04-03 20:24:52
海外TECH	CodeProject Latest Articles	Pathfinding Algorithms in C#	https://www.codeproject.com/Articles/1221034/Pathfinding-Algorithms-in-Csharp	astar	2023-04-03 20:18:00
海外TECH	CodeProject Latest Articles	Automating OpenOffice Calc from Visual Studio 2022 using C#	https://www.codeproject.com/Articles/5358229/Automating-OpenOffice-Calc-from-Visual-Studio-2022	language	2023-04-03 20:15:00
海外科学	NYT > Science	NASA Names Diverse Astronaut Crew for Artemis II Moon Mission	https://www.nytimes.com/2023/04/03/science/nasa-artemis-ii-moon.html	crucial	2023-04-03 20:32:38
海外科学	NYT > Science	Highlights From NASA’s Reveal of the Artemis II Moon Astronauts	https://www.nytimes.com/live/2023/04/03/science/artemis-nasa-news	artemis	2023-04-03 20:43:35
海外科学	NYT > Science	New Marburg Outbreaks in Africa Raise Alarm About the Deadly Virus’s Spread	https://www.nytimes.com/2023/04/03/health/marburg-outbreak-vaccine-treatment.html	New Marburg Outbreaks in Africa Raise Alarm About the Deadly Virus s SpreadThe spread of the Ebola like virus has claimed lives but could be a crucial chance to test a vaccine ーif supplies and researchers are mobilized in time	2023-04-03 20:00:57
ニュース	BBC News - Home	Nigel Lawson: Reforming chancellor dies aged 91	https://www.bbc.co.uk/news/uk-politics-65167914?at_medium=RSS&at_campaign=KARANGA	margaret	2023-04-03 20:57:38
ニュース	BBC News - Home	Darya Trepova: Russia releases video of suspect in cafe killing of Vladlen Tatarsky	https://www.bbc.co.uk/news/world-europe-65161095?at_medium=RSS&at_campaign=KARANGA	darya	2023-04-03 20:53:47
ニュース	BBC News - Home	Trump arraignment: Private plane, agents, protests expected on journey	https://www.bbc.co.uk/news/world-us-canada-65165590?at_medium=RSS&at_campaign=KARANGA	appearance	2023-04-03 20:01:51
ニュース	BBC News - Home	Chelsea: 'Difficult 24 hours' after Graham Potter sacking - Bruno Saltor	https://www.bbc.co.uk/sport/football/65165891?at_medium=RSS&at_campaign=KARANGA	graham	2023-04-03 20:46:35
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ビジネス	ダイヤモンド・オンライン - 新着記事	三菱商事・ENEOSが出資、「斜陽」のタクシー業界ベンチャーに大手が投資する理由 - Diamond Premium News	https://diamond.jp/articles/-/320662	三菱商事・ENEOSが出資、「斜陽」のタクシー業界ベンチャーに大手が投資する理由DiamondPremiumNewsタクシー会社のDXデジタルトランスフォーメーションを支援するベンチャーが、三菱商事やENEOSホールディングス傘下のファンドなどから出資を受けた。	2023-04-04 05:02:00
ビジネス	東洋経済オンライン	医師が警告！｢心臓に悪い"4つの油"に要注意だ｣ あなたが使っている｢その油｣､本当に大丈夫？ | 健康 | 東洋経済オンライン	https://toyokeizai.net/articles/-/659652?utm_source=rss&utm_medium=http&utm_campaign=link_back	東洋経済オンライン	2023-04-04 05:30:00
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