Oracle Layoffs: Over the weekend, numerous reports surfaced online, suggesting a large number of job cuts across Oracle, with 'several hundred' positions reportedly eliminated within OCI alone

Oracle Layoffs Sweep Through Cloud Division, Affecting Hundreds: Report

Panarin breaks tie on power play for New York, which will play Hurricanes or Islanders in 2nd Round

Rangers score twice in 3rd, sweep Capitals with win in Game 4 | NHL.com

For the Timberwolves, The trade for Rudy Gobert, Karl-Anthony Towns&#x27; value and Anthony Edwards&#x27; ascension all worked together, and it showed in the first round of the NBA playoffs.

Timberwolves trade for Rudy Gobert fooled many basketball analysts

Washington Capitals captain Alex Ovechkin, 38, took the blame for his team&#x27;s opening round sweep at the hands of the No. 1 seed New York Rangers on Sunday night, the first time the star winger ever went scoreless in a postseason series.

Capitals' Alex Ovechkin wary he 'didn't play well' in sweep - ESPN

MEXICO CITY -- The biggest reason the Astros have struggled in April is the health of their pitching staff. Six starters have already spent time on the injured list this season, including five at the same time. That forced Houston to call up some young arms who weren’t quite ready,

Framber Valdez logs five strong innings as Astros sweep Mexico City Series

Anthony Edwards scored 40 points, and Minnesota pulled away late to beat Phoenix and sweep the first-round playoff series.

Anthony Edwards puts up 40 as Timberwolves finish sweep of Suns - ESPN

A lot of the series was ugly — really, it was — and it is a compliment of the highest order to the Rangers that they were able to grind it through.

Rangers’ gritty sweep of Capitals was six months in the making

So, as the Capitals raised their sticks and saluted their fans following a 4-2 loss in Game 4 of the best-of-7 series that competed their sweep on Sunday, it was understandable to wonder how many more opportunities -- if any -- Ovechkin and what’s left of the Capitals’ Stanley Cup core ...

Capitals need to reevaluate, look to future after being swept in 1st round | NHL.com

Sweep

sweep

The United States v. Meta Platforms Court Filing October 24, 2023 is part of . You can jump to any part in this filing here. This is the table of links with all parts. HackerNoon’s Legal PDF Series : 4:23-cv-05448 Case Number Plaintiffs: State Of Arizona, The People Of The State Of California; State Of Colorado,; State Of Connecticut; State Of Delaware; State Of Georgia, Attorney General Of The State Of Georgia; State Of Hawai‘i, Ex Rel. Anne E. Lopez, Attorney General; State Of Idaho, Through Attorney General Raúl R. Labrador; The People Of The State Of Illinois; State Of Indiana; State Of Kansas, Ex Rel. Kris W. Kobach, Attorney General; The Commonwealth Of Kentucky; State Of Louisiana; State Of Maine; Office Of The Attorney General Of Maryland; State Of Michigan Ex Rel. Dana Nessel, Attorney General; State Of Minnesota, By Its Attorney General, Keith Ellison; State Of Missouri, Ex Rel. Andrew Bailey, Attorney General; State Of Nebraska Ex Rel. Michael T. Hilgers, Attorney General; Matthew J. Platkin, Attorney General For The State Of New Jersey, And Cari Fais, Acting Director Of The New Jersey Division Of Consumer Affairs; The People Of The State Of New York, By Letitia James, Attorney General Of The State Of New York; State Of North Carolina, Ex Rel. Joshua H. Stein, Attorney General; State Of North Dakota, Ex Rel. Drew Wrigley, Attorney General; State Of Ohio, Ex Rel. Attorney General Dave Yost; State Of Oregon Ex Rel. Ellen F. Rosenblum, Attorney General For The State Of Oregon; Commonwealth Of Pennsylvania By Attorney General Michelle A. Henry; State Of Rhode Island; State Of South Carolina, Ex. Rel. Alan M. Wilson, In His Official Capacity As Attorney General Of The State Of South Carolina; State Of South Dakota Ex Rel. Marty J. Jackley, South Dakota Attorney General; Commonwealth Of Virginia, Ex Rel. Jason S. Miyares, Attorney General; State Of Washington, Ex Rel. Robert W. Ferguson, Attorney General; State Of West Virginia, Ex Rel. Patrick Morrisey, Attorney General; And State Of Wisconsin, : Meta Platforms Defendant : October 24, 2023 Filing Date : Yvonne Gonzalez Rogers Judge : In the United States District Court for the Northern District of California Location TABLE OF CONTENTS I. SUMMARY OF THE CASE II. PUBLIC INTEREST III. JURISDICTION, VENUE AND DIVISIONAL ASSIGNMENT A. Jurisdiction B. Venue C. Divisional Assignment. IV. RELEVANT TIMES V. PLAINTIFFS VI. DEFENDANTS VII. TRADE AND COMMERCE IN THE FILING STATES VIII. META’S SCHEME TO EXPLOIT YOUNG USERS FOR PROFIT A. To maximize profit, Meta’s business model focuses on increasing young users’ engagement. 1. Meta monetizes young users’ attention through data harvesting and targeted advertising. 2. Meta specifically targets young users. 3. Meta designs and deploys features to capture young users’ attention and prolong their time on its Social Media Platforms. B. Meta falsely represents that its Social Media Platform features are safe and not designed to induce young users’ compulsive and extended use. Meta represents to the public that its Social Media Platforms are designed to support young users’ well-being. Meta prioritizes maximizing engagement over young users’ safety. Meta’s Recommendation Algorithms encourage compulsive use, which Meta does not disclose. The Recommendation Algorithms are harmful to young users’ mental health, notwithstanding Meta’s representations to the contrary. Meta’s use of social comparison features such as “Likes” also promotes compulsive use and mental health harms for young users. Meta’s use of disruptive audiovisual and haptic notifications interferes with young users’ education and sleep. Meta promotes Platform features such as visual filters known to promote eating disorders and body dysmorphia in youth Meta offers features that it claims promote connection between friends, but actually serve to increase young users’ time spent on the Platform. Through its Platform features, Meta discourages young users’ attempts to disengage, notwithstanding Meta’s representations to the contrary Meta knows its Platform features are addictive and harmful, but misrepresents and omits this information in public discourse. Meta makes its Platforms and associated harmful features available to especially young and vulnerable users. C. Meta has misled its users and the public by boasting a low prevalence of harmful content on its Social Media Platforms (Redacted) D. Meta’s Platform features cause young users significant physical and mental harm, of which Meta is keenly aware. IX. META’S COPPA NONCOMPLIANCE A. COPPA requires Meta to obtain verifiable parental consent for Instagram and Facebook users under the age of 13 B. Meta does not comply with COPPA with respect to Instagram. Meta possesses actual knowledge of children on Instagram and collects their personal information without obtaining parental consent. Instagram is “directed to children.” a. Instagram’s audience composition includes millions of users under the age of 13 b. Advertising that promotes Instagram and appears on Instagram is directed to children c. Meta’s design of the Instagram registration process allows children under 13 to use Instagram. d. Users under age 13 are an “intended audience” of Instagram. e. Subject matter, characters, activities, music, and other content on Instagram are child-oriented. f. Models and celebrities on Instagram are children and/or child-oriented. Meta does not obtain verifiable parental consent before collecting personal information from users under the age of 13 on Instagram. C. Meta does not comply with COPPA with respect to Facebook. Meta has actual knowledge of users under age 13 on Facebook. Facebook is “directed to children.” Meta does not obtain verifiable parental consent before collecting personal information from users under age 13 on Facebook. X. META CONTINUES TO EXPAND AND INTRODUCE NEW PLATFORMS XI. SUMMARY OF META’S DECEPTIVE AND UNFAIR OR UNCONSCIONABLE ACTS AND PRACTICES A. Deceptive Acts and Practices B. Unfair and/or Unconscionable Acts and Practices CLAIMS FOR RELIEF COUNT I: COPPA VIOLATIONS BY META COUNT II: VIOLATIONS OF THE ARIZONA CONSUMER FRAUD ACT, ARIZ. REV. STAT. §§ 44-1521 to -1534 COUNT III: FALSE OR MISLEADING STATEMENTS BY META IN VIOLATION OF BUSINESS AND PROFESSIONS CODE SECTION 17500 (BY THE PEOPLE OF THE STATE OF CALIFORNIA) COUNT IV: UNFAIR COMPETITION BY META IN VIOLATION OF BUSINESS AND PROFESSIONS CODE SECTION 17200 (BY THE PEOPLE OF THE STATE OF CALIFORNIA) COUNT V: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE COLORADO CONSUMER PROTECTION ACT, COLO. REV. STAT. § 6-1-105(1)(e) COUNT VI: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE COLORADO CONSUMER PROTECTION ACT, COLO. REV. STAT. § 6-1-105(1)(g) COUNT VII: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE COLORADO CONSUMER PROTECTION ACT, COLO. REV. STAT. § 6-1-105(1)(u) COUNT VIII: DECEPTIVE AND UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF THE COLORADO CONSUMER PROTECTION ACT, COLO. REV. STAT. § 6-1-105(1)(rrr) COUNT IX: VIOLATIONS OF THE CONNECTICUT UNFAIR TRADE PRACTICES ACT, CONNECTICUT GENERAL STATUTES § 42-110b et seq. COUNT X: VIOLATIONS OF THE DELAWARE CONSUMER FRAUD ACT (Delaware CFA), 6 Del. Code Ann. § 2513 et seq COUNT XI: VIOLATIONS OF THE DELAWARE DECEPTIVE TRADE PRACTICES ACT (Delaware DTPA), 6 Del. Code Ann. § 2531 et seq. COUNT XII: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF GEORGIA FAIR BUSINESS PRACTICES ACT, O.C.G.A. § 10-1-390 et seq COUNT XIII: UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF GEORGIA FAIR BUSINESS PRACTICES ACT, O.C.G.A. § 10-1-390 et seq. COUNT XIV: UNFAIR OR DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE HAWAI‘I UNFAIR AND DECEPTIVE ACTS OR TRADE PRACTICES ACT, HAW. REV. STAT. CHAPTER 480 COUNT XV: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE ILLINOIS CONSUMER FRAUD AND DECEPTIVE BUSINESS PRACTICES ACT, 815 ILCS 505/1 et seq. COUNT XVI: UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF THE ILLINOIS CONSUMER FRAUD AND DECEPTIVE BUSINESS PRACTICES ACT, 815 ILCS 505/1 et seq. COUNT XVII: CONDUCT VIOLATIVE OF THE ILLINOIS UNIFORM DECEPTIVE TRADE PRACTICES ACT BY META, IN VIOLATION OF THE ILLINOIS CONSUMER FRAUD AND DECEPTIVE BUSINESS PRACTICES ACT, 815 ILCS 505/1 et seq. COUNT XVIII: UNFAIR OR DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE INDIANA DECEPTIVE CONSUMER SALES ACT, IND. CODE § 24-5-0.5-3(a), -3(b)(1), AND -3(b)(2) COUNT XIX: KNOWING VIOLATIONS OF THE INDIANA DECEPTIVE CONSUMER SALES ACT AND INCURABLE DECEPTIVE ACTS, IND. CODE § 24-5-0.5-1 et seq. COUNT XX: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE KANSAS CONSUMER PROTECTION ACT, K.S.A. § 50-626 COUNT XXI: UNCONSCIONABLE ACTS OR PRACTICES BY META IN VIOLATION OF THE KANSAS CONSUMER PROTECTION ACT, K.S.A. §50-627 COUNT XXII: VIOLATIONS OF KENTUCKY CONSUMER PROTECTION ACT, KY. REV. STAT. CHAPTER § 367 et seq. COUNT XXIII: VIOLATIONS OF LOUISIANA UNFAIR TRADE PRACTICES AND CONSUMER PROTECTION LAW, LA. REV. STAT. ANN. §§ 51:1401 to 1428 COUNT XXIV: VIOLATIONS OF THE MAINE UNFAIR TRADE PRACTICES ACT, ME. REV. STAT. ANN. tit. 5, § 207 COUNT XXV: VIOLATION OF THE MICHIGAN CONSUMER PROTECTION ACT, MICH. COMP. LAWS § 445.901 et seq. COUNT XXVI: DECEPTIVE TRADE PRACTICES MINN. STAT. § 325D.43 et seq. COUNT XXVII: UNFAIR OR UNCONSCIONABLE ACTS MINN. STAT. § 325D.43 et seq. COUNT XXVIII: UNFAIR AND DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE MISSOURI MERCHANDISING PRACTICES ACT (MO. REV. STAT. § 407.020) COUNT XXIX: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE NEBRASKA CONSUMER PROTECTION ACT COUNT XXX: UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF THE NEBRASKA CONSUMER PROTECTION ACT COUNT XXXI: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE NEBRASKA UNIFORM DECEPTIVE TRADE PRACTICES ACT COUNT XXXII: UNCONSCIONABLE ACTS OR PRACTICES BY META IN VIOLATION OF THE NEBRASKA UNIFORM DECEPTIVE TRADE PRACTICES ACT COUNT XXXIII: VIOLATIONS OF THE NEW JERSEY CONSUMER FRAUD ACT, N.J. STAT. ANN. §§ 56:8-1 to 227 COUNT XXXIV: VIOLATION OF N.Y. GENERAL BUSINESS LAW § 349 COUNT XXXV: VIOLATION OF N.Y. GENERAL BUSINESS LAW § 350 COUNT XXXVI: REPEATED AND PERSISTENT FRAUD IN VIOLATION OF N.Y. EXECUTIVE LAW § 63(12) COUNT XXXVII: REPEATED AND PERSISTENT ILLEGALITY IN VIOLATION OF N.Y. EXECUTIVE LAW § 63(12) COUNT XXXVIII: VIOLATION OF FTC ACT § 5 IN VIOLATION OF N.Y. EXECUTIVE LAW § 63(12) COUNT XXXIX: VIOLATIONS OF THE NORTH CAROLINA UNFAIR OR DECEPTIVE TRADE PRACTICES ACT, N.C.G.S. § 75-1.1 (BY STATE OF NORTH CAROLINA) COUNT XL: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF N.D. CENT. CODE §51-15-02 (BY NORTH DAKOTA) COUNT XLI: UNLAWFUL ACTS OR PRACTICES BY META IN VIOLATION OF N.D. CENT. CODE §51-15-02 (BY NORTH DAKOTA) COUNT XLII: VIOLATIONS OF OHIO CONSUMER SALES PRACTICES ACT – UNFAIR OR DECEPTIVE ACTS OR PRACTICES - OHIO REVISED CODE § 1345.02 COUNT XLIII: VIOLATIONS OF OHIO CONSUMER SALES PRACTICES ACT – UNCONSCIONABLE CONSUMER SALES ACTS OR PRACTICES - OHIO REVISED CODE §1345.03 COUNT XLIV: VIOLATIONS OF OREGON’S UNLAWFUL TRADE PRACTICES ACT (UTPA), O.R.S. § 646.607(1) COUNT XLV: VIOLATIONS OF OREGON’S UTPA, O.R.S. § 646.608(1)(e) COUNT XLVI: VIOLATIONS OF OREGON’S UTPA, O.R.S. § 646.608(1)(t) COUNT XLVII: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF THE PENNSYLVANIA UNFAIR TRADE PRACTICES AND CONSUMER PROTECTION LAW (UTPCPL) COUNT XLVIII: UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF THE PENNSYLVANIA UNFAIR TRADE PRACTICES AND CONSUMER PROTECTION LAW (UTPCPL) COUNT XLIX: VIOLATIONS OF RHODE ISLAND DECEPTIVE TRADE PRACTICES ACT, R.I. GEN. L. §§ 6-13.1-1 TO 6-13.1-10 COUNT L: VIOLATION OF THE SOUTH CAROLINA UNFAIR TRADE PRACTICES ACT, S.C. CODE ANN. SECTION 39-5-10 et seq. COUNT LI: VIOLATIONS OF VIRGINIA CONSUMER PROTECTION ACT, VA. CODE §§ 59.1-198 TO 59.1-207 COUNT LII: DECEPTIVE ACTS OR PRACTICES IN VIOLATION OF THE WASHINGTON CONSUMER PROTECTION ACT, WASH. REV. CODE § 19.86.020 COUNT LIII: UNFAIR ACTS OR PRACTICES BY META IN VIOLATION OF THE WASHINGTON CONSUMER PROTECTION ACT, WASH. REV. CODE § 19.86.020 COUNT LIV: DECEPTIVE ACTS OR PRACTICES BY META IN VIOLATION OF WISCONSIN’S DECEPTIVE TRADE PRACTICES ACT, WIS. STAT. § 100.18(1) PRAYER FOR RELIEF About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:23-cv-05448 retrieved on October 24, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. Washingtonpost.com

Meta Platforms Face Sweeping Multi-State Legal Action Over Child Safety Violations

"Sweep them! Sweep them!"

In a crypto wallet whose password has been hacked and a bot has been installed on the account, the $26,000 pending stake can be stolen at any time.🤖 In the Dark Forest of the Blockchain, I will tell you the story of our fight against HackerBot, the victory with "Bot19", which is faster and sharper than the one I coded, and the $26,000 token I saved. My specialist is smart contract coding, I also love solving the toughest problems of blockchain, so I also do recovery of stuck-tokens from compromised accounts I first read the concept of "Blockchain Dark Forest" in 2020 in this article by Dan Robinson and was very impressed. https://wwwparadigma.xyz/2020/08/ethereum-is-a-dark-forest is one of the most talented people in the blockchain space in the world. In this article, he tells us wonderfully about a battle with a bot on the Ethereum network, the defeat that followed, and the lessons to be learned from it. This article has had a great impact on me in fighting bots. Dan Robinson I get at least 5 messages a day from my Twitter account from victims whose accounts have been hacked and bots are connected to their accounts. Recently, I received a message from a user, he entered a fake site that should not have entered the seed words by mistake and panicked and had his seeds stolen. Afterward, the tokens in his account were immediately emptied by the hacker. However, the 26K$ in stakes has not yet been discovered by the hacker. I immediately accepted the half request and immediately began to investigate. A bot was linked to the stolen account by the hacker. This bot, when you send BNB tokens to the account for fee, it instantly sweeps them and sends them to the hacker account. (Hackers, airdrops, stakes, LPs, etc.) always connect bots to the account to steal possible tokens, remember these are professional thieves, this is their job) ⏳ Problem: In the Bsc blockchain, an account has $26k worth of staking in cryptocurrencies, the hacker can spot it anytime and absolutely nothing can be done due to the bot in the account. 🎯 Solution: Write a faster bot than HackerBot, launch an attack, take the coins from the staking before Hackerbot and move them to a secure wallet I immediately started designing "Bot19" for the rescue, I knew from my past experience what I had to do. A coding time is spent in the following schedule for me: 70% Designing the Architecture + 30% Writing the Code HackerBot First of all, I write the things that need to be done on a Cheklist and they are done respectively, I like the way I do business :) ✅ 1- Synchronization between nodes in 1-BSc network is problematic, so I have to set up my own node and run my bot there ✅ 2- I have to calculate the reaction times of HackerBot and write a faster bot than these times ✅ 3- My transactions must be atomic, so they are all simultaneous, the slightest time gap means that I deliver the funds to HackerBot ✅ 4- Which Blockchain network you are fighting, the block structure of that network, block priority, transaction priorities, etc. you have to have a lot of serious knowledge and experience, I will review everything on this subject again. ✅5- Tests are very important, no matter what I code, the blockchain that is closed to the outside world will also test it and I will definitely see its success in the tests. Designing the Bot Architecture: 1- If you are going to write code about stake, you should know how LP Pairs work very well in terms of technique and coding. 2-It is important to calculate the value of the fund to be saved as LP correctly, we get this value from the LP contract. 3- You need a fast node for the transaction, which is to set up your own node; https://medium.com/@pieterc/running-a-full-node-with-geth-bsc-610085141248 4-For a bot with fast and Atomic processing capability; We can deploy Contract in blockchain and manage it remotely with Javascript library. The Ether.js library is a technology that bot operators should know very well. Ether.js 5-For your bot to be very fast, it is not enough to have good code, it should be fast and seamless on the hardware you use. For this we have to use Amazon Web Services 6- It is an inaccurate method to manually follow the staking expiry times of the tokens in staking, we must follow this and ensure that our bot automatically processes it at the end of staking. 7- Test: If you are writing blockchain code, you definitely know how important the test is. In this process, we optimize our bot according to the test results. Sample Bot Test code; https://github.com/AleRapchan/flash-swap-arbitrage-bot/blob/main/test/dai.js I will not go into technical information, we wrote our codes with 160 pages of technical preparation, now it's time for the war. We have very little time It's Time to Go To War And we run our bot, it's coded to do all the operations atomically; Firstly, sending a fee to the account for transactions+ Removal of LP Stakings + Transfer of Unstaking tokens to a secure wallet and all this before HackerBot And happy ending, we managed to move all the tokens to the safe address 😅🎉🎊 We are the winners this time in the dark forest of blockchain 🎯 Conclusion Your wallet seeds are very important and you should definitely keep them safe. If you want to support or brainstorm about the funds that need to be recovered from the hacked accounts, you can send me a message on my twitter account.

How Did We Bypass the Sweeper Bot and Saved $26K Tokens in the Dark Forest of Blockchain ?

Lead image via Guap The term ‘smart textiles’ comes from the idea of intelligent or smart materials. In 1989, from Japan, smart materials were based on the very first textile made of silk thread which has shape memory, and the innovation continued on. In the 1960’s polymeric gels were made and came in the birth of more smart textiles. Offering products that benefit users with it’s technical abilities. The industry of smart textiles is ever-growing as it not only applied in the military and medical field but in the fashion industry as well. Where designers adopt smart textiles in expressing certain inspiration to contemporary society.  The market of smart fabrics and textiles is said to grow hugely in the upcoming years from 2021 to 2026. Expressing the huge potential and future smart textiles have to offer What are smart textiles? Smart textiles are basically fabrics and materials with added value through technology that enhances a users physical or aesthetic aspect. Initially, smart textiles were used in Military, Civil, and Healthcare uses. There are two types of Smart textiles Passive Smart textiles That can only sense the current atmosphere or environment , which are usually sensors Active Smart textiles Can sense the stimuli from the environment and provide a reaction to it. In addition to its sensor function it also has the actuator function. Gif via Pinterest The Market According to a report, which investigates the current landscape of the smart textile business sector and its future effects due to COVID-19. The global market was $2518.9 million in 2019 and is expected to be $7881.6 million by the end of 2026. Provided in the following categories, where 31% is allocated to military, 34% to civil, 17% to healthcare during 2016. The fashion industry has been joining this market and growing steadily. What makes textiles “SMART” Based on their specific purpose, smart textiles are created through ingraining fibers and different technologies. Some fibers have conductive aspects and polymers, even shape memory, fiber optics, and additional novel technological enhancements. SensorsChemical treatmentsThermochromic dyesThese materials interact with one another along with an external stimuli — such as temperature, light or pressure — creating a transfer of energy. Once activated, the functional fabric responds depending upon the textile’s function. Image via Ilovemcqueen What is their purpose? Smart textiles usually are in two categories which have their own purpose to solve or improve current issues in both the industrial and fashion industry. Aesthetics Smart fabric has been steadily adopted in the fashion industry. Providing beautiful pieces that voice out certain inspiration and elements. Through changing color and interactive elements that allow fashion designers to showcase a different form of fashion Image via Dezeen Performance enhancement Focuses more on the performance of the textile allowing enhancement in more specific form such as temperature, reducing wind and water resistance, space travel and vibration of muscles. Fashion and Smart Textiles CalmWear Is one brand that uses compression clothing to ease hypersensitivity, it usually works on symptoms of ADHD, sensory processing disorder and many more Lumen Couture Has several collections of distinct uses of smart textiles in LED allowing moving bright shapes to appear on their clothing and accessories. Emel + Aris heating technology Creating outerwear and mixing it with heating technology, creates smart outerwear in general. Allowing one to warmly walk out during cold seasons Benefits What other way but to convince you with the benefits of smart textiles: Sensors can help track and alert users, aside from this the fabric can respond to muscle vibrations making sure that it is the correct form, reducing risk of injury Helps improve the quality of life for individuals with disabilities. Smart textiles can help enhance the capacity of stimuli such as compression clothing and regulators. Long-term items, although expensive, may be timeless pieces that aid in everyday life. Gif via Giphy The Verdict Smart textiles have this great potential to improve both the fashion wave and the quality of life of an individual. Introducing a new world that is steadily growing.

Smart Textiles are Sweeping the Fashion Industry

Operation Crypto Sweep On Monday, North American Securities Administrators Association (NASAA) announced one of the largest coordinated series of securities enforcement actions ever. If you have been following the crypto space over the last two years, this should not come as a surprise. In fact, this weeks actions were inevitable. Still, the scope of this so-called ‘Operation Cryptosweep’ is massive. The hunt is on For some time, regulators have been warnings to investors and issuers to be careful. The Securities and Exchange Comission (SEC) . Recently, they even launched to teach investors a lesson. What a time to be alive. issuing set up a special Cyber Taskforce a fake ICO website This week’s actions however, came from the SEC’s smaller brothers and sisters at the state level. Although these regulators get far less attention in the ICO space than the SEC, they too have jurisdiction to combat securities fraud. Working together in the North American Securities Administrators Association (NASAA), these state regulators launched ‘Operation Cryptosweep’, which to date has resulted in nearly 70 inquiries and investigations and 35 pending or completed enforcement actions related to ICOs or cryptocurrencies since the beginning of May. And, as NASAA President Joseph Borg has stated: “The actions announced today are just the tip of the iceberg.” — Borg What’s the deal? Many projects in the crypto-space started using a new way of fundraising, Initial Coin Offerings (ICOs), to fund their businesses. In an ICO, a business sells crypto-tokens to retail investors. Any funds raised during the sale are subsequently used to develop the underlying platform / business where the tokens can be used. Investors hope that, once demand for the utility of the platform increases, the value of the token increases as well, as the supply of tokens is limited. There are, however, a number of with this practice: problems Information asymmetries between issuer and investor Lack of guarantees that the issuer’s promises will be fulfilled Fraudulent issuers that scam investors out of their money Of course, these problems are not new. In fact, they are the reasons why we have developed securities legislation over the last 80 years. When one sells an investment contract (such as a token), he generally has to register with the relevant securities regulator and provide certain information to investors in the form of a prospectus. For ICOs however, this rarely happens and many issuers are thus committing borderline securities fraud. As such, an initial batch of over 30 have been sent to ICO issuers, with more investigations and enforcement actions on the way. Cease and Desist letters Inquiry Into Crypto-Exchanges It should be noted that the sights of the regulators are not merely aimed at ICO issuers. Notable are the that have been sent to crypto exchanges. According to the letters, the platforms often lack the basic market protections of traditional investing platforms. At the same time, the extent of disclosures to customers about trading rules, internal controls, and other basic practices varies from platform-to-platform, making it difficult or impossible for prospective users to evaluate the actual risks of trading on a particular platform. Therefore, Attorney General Schneiderman has requested the exchanges to fill in the information demand letters this three page questionaire. Below you will find the list of exchanges and ICO issuers against which actions have been taken. List of targeted exchanges Edit: List does not properly display everything. Here is the rest: Gemini Trust Company Huobi Global Limited iFinex Inc. (Bitfinex) itBit Trust Company Orca Alliance Payward, Inc. (Kraken) List of targeted ICO issuers About the Author: Thijs Maas is a LLM student with a healthy obsession for the legal challenges that arise in relation to the wave of innovation brought by distributed ledger technologies. He launched www.lawandblockchain.eu , a website that acts as a hub for information, insights and academic research on the subject.

Regulators on the hunt: Operation Crypto Sweep has begun.

I have to admit, I am in quite the unique position in my journey of ‘job-hunting.’ Unfortunately, I won’t share it yet given that I am still ‘experiencing it’ and like any storyteller, we would like to share the whole story once it has ended so that we can reflect on it. However, in the midst of intensely ‘networking’ and being active by writing messages on LinkedIn, I have to say From the moment I graduated, I had not coded till now and having experienced this, my fingers have gotten dusty. I recommend you not to do this. You start feeling your fingers crack as you begin to type more actively while you feel the wires sparking in your mind, trying to remember all that you learnt. It’s painful and regretful I would say. However, it is totally understandable given it is difficult for one to code in such stressful times. Especially when jobs are something our lives somewhat depend on. So, then comes the question given that the route many of us takes is this one: “How does one get back into coding” Well, if there’s another way to explain the situation, it’s like exercising. People who have very attractive and fit bodies exercise regularly but the moment they stop exercising for a day, they feel the burdens on their shoulders whilst they attempt to workout again. It gets even worse when you wait for a longer period of time and then realise that it’s even harder to start again than it was before. However, it’s not impossible and the most important thing once we have been through the factory of coding, is to simply practice, practice and practice. Setting up a learning plan: Given I’ve just stated the above, I believe the best solution that I have come across so far is setting up a learning plan. It sounds very daunting given that there’s an oyster of technologies to learn in the sea. How does one prioritise what to learn? How does one discipline themselves to code every day? Where does even one begin with planning? My coding bootcamp has ended…What happens now? When many of us think about setting up a learning plan, it seems like a struggle to choose. Life would be so much easier or quicker if we could choose between two flavours of ice-cream rather than a row of 50 ice-cream flavours right? Think about it. We would be able to taste our chosen flavour rather than spend hours trying to pick a flavour we really can savour (see what I did there) However, I’ve learnt over the few days that procrastination and voice empowerments that all the questions above doesn’t matter. What matters is that we do, by which is write code everyday. Of course, then the next dilemmas come of and what we choose to do how far of a stretch do we want to take our rusty skills. Me with all the things I wanted to learn I can say for first few days, I struggled hard to build projects. I remembered the concepts and what comes next, but to actually remember the syntax and solve it step by step gave my fingers the shivers. It was like seeing a machine covered in moss trying to run with the gunk inside it. I knew that if the struggle would be too real and hard, I would never want or to start to code again. Hence, I needed to find a better way. For me, abetter way was to implement a smaller task. As long I kept writing code everyday, that was already a step forward. Hence, to those of you who is taking this title’s advice, my advice for it would be to and start small be okay with yourself starting small. I know when we all come out of a bootcamp that we want to do cool projects, and show off all these cool skills and amazing things we can do. However, you are not going to move forward or find it very difficult to do so if you run before you can walk. Like exercise, you can’t just go do 50 push-ups when you haven’t do push-ups in 5 months. The pain will be real and you won’t find the motivation to keep going anymore. In other words, it’s better to try take a baby step everyday for 500 days than take 100 steps and fall flat. Consistency in progress is the best progress. Starting tips to get back on your feet: In my week experience of trying to get myself to code, I am currently following some post-course material that coaches wrote. I have to say it is very useful to have a guide that will get rid of the rust in your gears. Although the to get my gears up and running are only for two weeks, it sets out a list of things you could do to get you motivated to code projects. It also give you the drive to set out to plan your own learning plan, which is the vital point all developers want to be at. Now, I don’t have all the solutions and I’m sure there are more out there but these are my options in case I ever get stuck. programme If you know there’s a link to a post-course somewhere, do it! It’ll help you get on your feet and plus, it’s nice to see the two bullet points on your list completed. Appreciate what you have done rather than sulk on the many things you have to do. Why not reflect about your skills? Write all the you know and rate it out of 1 to 10. See what are your stronger points and weaker points. Then, make a decision to do a kata base on your language preference and skills. technologies Write a list of coders that inspire you and write why these people inspire you. I find having a mentor sets a somewhat bar of how skilled you want to be. Is it their approach? Is it their discipline? Is it what they read? Perhaps, write the skills that you think you have and what skills as a developer you would like to have. It could not even be about code but commuting to the tech community. Do Katas! There’a bunch of katas on code-wars or if you search on Google, that are small projects. You might look at these and think, piece of cake but here I sit doing the “String Calculator” having done only two steps in three days when there are nine. Do a Udemy course that builds projects whilst teaching the language! Udemy courses are great for learning languages or areas of code that you weren’t sure about. It also gives you more projects to show your passion on Github. Do a collaboration with one of your friends or another developer? If it’s hard to motivate yourself, get someone else to work with you so the journey can be more fun! Yeah, I know what you are thinking. Why do katas? Why have a repo that sets up a framework? Why have something that can’t be even counted as a project? I am a victim of these thoughts as well but I can concluded that to show progress is valuable. You never know, maybe your repo might be a helpful guide for someone learning how to code or maybe your repo might be more important to others more than you know it! Unless you are tracking and know exactly what people are doing with your repos, or looking at your repos or even just looking on your Github, you never know. And believe me, it’s great to live for the unexpected surprises then live with decisions we for sure aren’t certain about. So, I sit here with you (if you are a developer) and pledge: no more excuses. Whether you stopped yesterday, the past few days, weeks or months, it doesn’t matter! We have time and yes, it’s hard getting back into it but our coding skills that need our care for them to grow is somewhere still in us. After all, if we did a bootcamp, our coding skills have not disappear. They are just covered in dust that all we have to do, is sweep it away. Let’s take baby steps and get coding! Fun fact of the day: Coming from a creative background, I really see the similarities in both design and code. After all, they are both ‘tool industries’ that will keep adapting and require time for one to really get into their craft. Having connected and talked with so many others from big or small companies about this matter, I can confidently argue that and so it’s normal to feel a blockage. It’s normal to feel you need a break to refresh your senses and replenish your ideas. coding is a creative process It’s all part of the progress, and just to emphasise my point on how progress matters, in design, that is what a creative process is all about. Progress. Companies and clients like to talk about the process of ideas, how you think and the variety of approaches you had to solve the problem. In fact, it’s much more interesting for them in the sense that it shows you how far you’ve come in your work and how you create, as a creative. Given I have strongly argued that creative processes are about showing the progress (or in a cliche way, ‘the journey’), this makes it okay to feel blockages and makes it okay to show unfinished projects or small things. We should always remember progress is what matters, even in the little things we do so start appreciating the baby steps today, can keep appreciating them everyday.

Episode 47: How to sweep your dusty fingers and keep active to code

Why Everyone is Wrong About the Future of Work™

কেন সবাই কাজের ভবিষ্যত সম্পর্কে ভুল ™

Warum alle falsch liegen, wenn sie über die Zukunft der Arbeit sprechen™

Por qué todo el mundo está equivocado sobre el futuro del trabajo™

Pourquoi tout le monde se trompe sur l’avenir du travail™

काम के भविष्य के बारे में हर कोई गलत क्यों है™

誰もが仕事の未来について間違っている理由™

왜 모든 사람이 미래의 일에 대해 틀렸는가?™

Por que todos estão errados sobre o futuro do trabalho™

Почему все ошибаются относительно будущего работы™

Neden Herkes Çalışmanın Geleceği Hakkında Yanılıyor?™

Tại sao mọi người đều sai về tương lai của công việc™

为什么每个人对工作的未来都有误解™

Now that we've covered the US presidential elections and most of the Q3 earnings, I want to take a moment to discuss Intel and some of the excellent reporting from Reuters about the company's downfall. Intel, as it is today, appears very insignificant when compared to AMD and Nvidia, both of whom have made some very shrewd bets on artificial intelligence, especially Nvidia. Though in Nvidia's case, I've argued that its technology was simply at the right place at the right time. As I said so in March: Nvidia never really started as an artificial intelligence company the way OpenAI and so many others like it did. It started out as a company that produced graphic cards for video games, and for a long, long time, this is what Nvidia was known for. But as an offshoot of all the research it did in producing better and better graphic cards, it ended up creating tensor cores for real-time deep learning image enhancement and upscaling technologies for use in video games. Little did Nvidia know that this technology would then serve as the backbone of LLMs, instantly transforming it as the arms dealer of choice in corporations' pursuit of the perfect AI. At the time Nvidia was developing its technology, however, Intel engineers were scoffing at video gaming chip architecture and believed that a CPU could more effectively handle processing tasks needed to build and run AI models. As time has bore witness, Intel and its engineers were wrong. Very, very wrong. So when demand for AI chips skyrocketed, Intel was left with its pants down, scrambling to get a product out. Ironically, Intel was this close to hitting the jackpot that Nvidia eventually ended up striking. In 2017 and 2018, the company had the opportunity to invest in OpenAI but decided against it because then-CEO Bob Swan did not believe generative AI would make it to the market soon enough for it to be worthwhile the $1 billion Intel would have had to pay for a 15% stake. OpenAI also offered a further 15% stake if Intel agreed to make hardware for it at cost price — but the company refused, leaving OpenAI to rely on Nvidia's chips instead. GET PUBLISHED ON HACKERNOON.
Join a global network of 45,000+ published devs, builders,   founders, makers, VCs, hodlrs, and hackers. Start submitting your tech   stories and tutorials to get published FREE on HackerNoon — no pop-ups,   no paywalls. But that was then. Intel hasn't fared any better under current CEO Pat Gelsinger's leadership either. Intel rehired Gelsinger in 2021 to help lead the company out of a tough spot: it was losing out to the likes of Taiwan Semiconductor Manufacturing and Samsung Electronics on chip-making technology, and the idea was to have Gelsinger, who had been with Intel for most of his career and helped develop some of its most successful personal-computer chips, lead a turn around. While Gelsinger's heart was in the right place, his turnaround plan didn't really do much to turn the company's fortunes around. In fact, things came to a head this past summer when Intel stunned both employees and investors with its poor quarterly results and announced sweeping measures (cost cuts, headcount reduction, etc.) to become profitable again. All of this could have been avoided had it not been for some key mistakes Gelsinger made after taking reins of the company. According to Reuters, soon after becoming CEO, Gelsinger offended Taiwan Semiconductor Manufacturing by calling Taiwan unstable. Gelsinger's "Taiwan is not a stable place" comment had more to do with his push to develop a US-based supply chain for chip manufacturing, but was so poorly received by TSMC that it reneged on a 40% discount it was willing to offer Intel on chips it designed but could not produce. That discount would have really helped Intel's margins, but, nope, Gelsinger was too busy commenting on Taiwan. Making matters worse, Gelsinger kept doubling down on his plan to develop a manufacturing footprint that could rival TSMC's, but on American and European soil instead. Problem is, customers have no reason to shy away from TSMC, particularly considering that Intel's foundry ambitions have run into technical challenges. Combined with the fact that Intel kept sticking to producing chips for desktop computers and servers, and you have a clearer picture of why the company is in such dire straits today. The list of fumbles goes on, but what must really make this sting for Gelsinger is that just a few weeks ago it was announced that Nvidia would take the company's place on the Dow Jones Industrial Average. Today, Nvidia is the most valuable company in the world. The company has a pile of cash. And CEO Jensen Huang's 3.8% stake in Nvidia is worth more than Intel's market value combined, Reuters reports. And to think Intel could have prevented all of this from happening. The way I see it, Intel is either going to be bought or Gelsinger will be fired, possibly both. I'll be here to report on it when it happens. Intel was #198 on HackerNoon's Tech Company Rankings this week. In Other News.. 📰 Bitcoin ETF Options Attract $2B on Day One, Shifting BTC’s Market Structure — via CoinDesk
H, the AI startup that raised $220M, launches its first product: Runner H for ‘agentic’ applications — via TechCrunch
With Musk in tow, Trump eyes changes to government policies on AI and its dangers — via CNN
Apple to urge judge to end US smartphone monopoly case — via Reuters
Trump 2.0 will face Big Tech antitrust test — via Axios
FTX co-founder Gary Wang avoids prison time for role in crypto fraud — via CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan, Editor, Business Tech @ HackerNoon *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Now that we've covered the US presidential elections and most of the Q3 earnings , I want to take a moment to discuss Intel and some of the excellent reporting from Reuters about the company's downfall. US presidential elections US presidential elections Q3 earnings Q3 earnings Intel Intel Intel, as it is today, appears very insignificant when compared to AMD and Nvidia , both of whom have made some very shrewd bets on artificial intelligence, especially Nvidia. Though in Nvidia's case, I've argued that its technology was simply at the right place at the right time. AMD AMD Nvidia Nvidia As I said so in March: said said Nvidia never really started as an artificial intelligence company the way OpenAI and so many others like it did. It started out as a company that produced graphic cards for video games, and for a long, long time, this is what Nvidia was known for. But as an offshoot of all the research it did in producing better and better graphic cards, it ended up creating tensor cores for real-time deep learning image enhancement and upscaling technologies for use in video games. Little did Nvidia know that this technology would then serve as the backbone of LLMs, instantly transforming it as the arms dealer of choice in corporations' pursuit of the perfect AI. Nvidia never really started as an artificial intelligence company the way OpenAI and so many others like it did. It started out as a company that produced graphic cards for video games, and for a long, long time, this is what Nvidia was known for. But as an offshoot of all the research it did in producing better and better graphic cards, it ended up creating tensor cores for real-time deep learning image enhancement and upscaling technologies for use in video games. Little did Nvidia know that this technology would then serve as the backbone of LLMs, instantly transforming it as the arms dealer of choice in corporations' pursuit of the perfect AI. Nvidia never really started as an artificial intelligence company the way OpenAI and so many others like it did. It started out as a company that produced graphic cards for video games, and for a long, long time, this is what Nvidia was known for. But as an offshoot of all the research it did in producing better and better graphic cards, it ended up creating tensor cores for real-time deep learning image enhancement and upscaling technologies for use in video games. Little did Nvidia know that this technology would then serve as the backbone of LLMs, instantly transforming it as the arms dealer of choice in corporations' pursuit of the perfect AI. At the time Nvidia was developing its technology, however, Intel engineers were scoffing at video gaming chip architecture and believed that a CPU could more effectively handle processing tasks needed to build and run AI models. scoffing scoffing As time has bore witness, Intel and its engineers were wrong. Very, very wrong. So when demand for AI chips skyrocketed, Intel was left with its pants down, scrambling to get a product out. Ironically, Intel was this close to hitting the jackpot that Nvidia eventually ended up striking. In 2017 and 2018, the company had the opportunity to invest in OpenAI but decided against it because then-CEO Bob Swan did not believe generative AI would make it to the market soon enough for it to be worthwhile the $1 billion Intel would have had to pay for a 15% stake. this OpenAI OpenAI OpenAI also offered a further 15% stake if Intel agreed to make hardware for it at cost price — but the company refused, leaving OpenAI to rely on Nvidia's chips instead. GET PUBLISHED ON HACKERNOON. Join a global network of 45,000+ published devs, builders,   founders, makers, VCs, hodlrs, and hackers. Start submitting your tech   stories and tutorials to get published FREE on HackerNoon — no pop-ups,   no paywalls. GET PUBLISHED ON HACKERNOON. GET PUBLISHED ON HACKERNOON . GET PUBLISHED ON HACKERNOON Join a global network of 45,000+ published devs, builders,   founders, makers, VCs, hodlrs, and hackers. Start submitting your tech   stories and tutorials to get published FREE on HackerNoon — no pop-ups,   no paywalls. Join a global network of 45,000+ published devs, builders,   founders, makers, VCs, hodlrs, and hackers. Start submitting your tech   stories and tutorials to get published FREE on HackerNoon — no pop-ups,   no paywalls. But that was then. Intel hasn't fared any better under current CEO Pat Gelsinger's leadership either. Intel rehired Gelsinger in 2021 to help lead the company out of a tough spot: it was losing out to the likes of Taiwan Semiconductor Manufacturing and Samsung Electronics on chip-making technology, and the idea was to have Gelsinger, who had been with Intel for most of his career and helped develop some of its most successful personal-computer chips, lead a turn around. rehired rehired While Gelsinger's heart was in the right place, his turnaround plan didn't really do much to turn the company's fortunes around. In fact, things came to a head this past summer when Intel stunned both employees and investors with its poor quarterly results and announced sweeping measures (cost cuts, headcount reduction, etc.) to become profitable again. stunned stunned All of this could have been avoided had it not been for some key mistakes Gelsinger made after taking reins of the company. According to Reuters, soon after becoming CEO, Gelsinger offended Taiwan Semiconductor Manufacturing by calling Taiwan unstable. According According Gelsinger's "Taiwan is not a stable place" comment had more to do with his push to develop a US-based supply chain for chip manufacturing, but was so poorly received by TSMC that it reneged on a 40% discount it was willing to offer Intel on chips it designed but could not produce. That discount would have really helped Intel's margins, but, nope, Gelsinger was too busy commenting on Taiwan. Making matters worse, Gelsinger kept doubling down on his plan to develop a manufacturing footprint that could rival TSMC's, but on American and European soil instead. Problem is, customers have no reason to shy away from TSMC, particularly considering that Intel's foundry ambitions have run into technical challenges. Combined with the fact that Intel kept sticking to producing chips for desktop computers and servers, and you have a clearer picture of why the company is in such dire straits today. The list of fumbles goes on, but what must really make this sting for Gelsinger is that just a few weeks ago it was announced that Nvidia would take the company's place on the Dow Jones Industrial Average. announced announced Today, Nvidia is the most valuable company in the world. The company has a pile of cash. And CEO Jensen Huang's 3.8% stake in Nvidia is worth more than Intel's market value combined, Reuters reports . reports reports And to think Intel could have prevented all of this from happening. The way I see it, Intel is either going to be bought or Gelsinger will be fired, possibly both. I'll be here to report on it when it happens. Intel was #198 on HackerNoon's Tech Company Rankings this week. In Other News.. 📰 In Other News.. 📰 Bitcoin ETF Options Attract $2B on Day One, Shifting BTC’s Market Structure — via CoinDesk H, the AI startup that raised $220M, launches its first product: Runner H for ‘agentic’ applications — via TechCrunch With Musk in tow, Trump eyes changes to government policies on AI and its dangers — via CNN Apple to urge judge to end US smartphone monopoly case — via Reuters Trump 2.0 will face Big Tech antitrust test — via Axios FTX co-founder Gary Wang avoids prison time for role in crypto fraud — via CNBC Bitcoin ETF Options Attract $2B on Day One, Shifting BTC’s Market Structure — via CoinDesk CoinDesk CoinDesk H, the AI startup that raised $220M, launches its first product: Runner H for ‘agentic’ applications — via TechCrunch TechCrunch TechCrunch With Musk in tow, Trump eyes changes to government policies on AI and its dangers — via CNN CNN CNN Apple to urge judge to end US smartphone monopoly case — via Reuters Reuters Reuters Trump 2.0 will face Big Tech antitrust test — via Axios Axios Axios FTX co-founder Gary Wang avoids prison time for role in crypto fraud — via CNBC CNBC CNBC And that's a wrap! Don't forget to share this newsletter with your family and friends! See y'all next week. PEACE! ☮️ — Sheharyar Khan , Editor, Business Tech @ HackerNoon Sheharyar Khan Sheharyar Khan *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. *All rankings are current as of Monday. To see how the rankings have changed, please visit HackerNoon's Tech Company Rankings page. Tech Company Rankings Tech Company Rankings Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here. Tech, What the Heck!? is a once-weekly newsletter written by HackerNoon editors that combine HackerNoon's proprietary data with news-worthy tech stories from around the internet. Humorous and insightful, the newsletter recaps trending events that are shaping the world of tech. Subscribe here . here here

Intel (No Longer) Inside, or How One CEO Messed Everything Up

ইন্টেল (আর নেই) ভিতরে, বা কীভাবে একজন সিইও সবকিছুকে গোলমাল করেছে

Intel (nicht mehr) Inside oder wie ein CEO alles vermasselt hat

Intel (ya no está) dentro, o cómo un CEO lo arruinó todo

Intel (n'est plus) à l'intérieur, ou comment un PDG a tout gâché

इंटेल (अब नहीं) अंदर, या कैसे एक सीईओ ने सब कुछ गड़बड़ कर दिया

インテル（もはや）内部、あるいはある CEO がいかにしてすべてを台無しにしたか

Intel(더 이상) 내부 또는 한 CEO가 모든 것을 어떻게 망쳤는지

Intel (não mais) dentro, ou como um CEO bagunçou tudo

Intel (больше не) Inside, или как один генеральный директор все испортил

Intel (Artık) İçeride Değil veya Bir CEO Her Şeyi Nasıl Mahvetti

Intel (Không Còn) Bên Trong, hay Một CEO Đã Làm Hỏng Mọi Thứ Như Thế Nào

英特尔（不再）内部，或者一位首席执行官如何把一切都搞砸了

We Analyzed 20.2 Million CI Jobs In Trunk Flaky Tests: Here's What We Learned - Part 1

Authors:
(1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work;
(2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work;
(3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University;
(4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Table of Links Abstract and 1 Introduction 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field 2.2 The Detector Signal 3 Statistical Analysis and 3.1 Signal Likelihood 3.2 Projected Exclusions 4 Application to Accelerometer Studies 4.1 Recasting Generalised Limits onto B − L Dark Matter 5 Future Directions 6 Conclusions, Acknowledgments, and References A Equipartition between Longitudinal and Transverse Modes B Derivation of Marginal Likelihood with Stochastic Field Amplitude C Covariance Matrix D The Case of the Gradient of a Scalar 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field With non-linear gravitational clustering, we expect an equipartition of longitudinal and transverse helicities of the plane waves in our vicinity, regardless of whether the early universe production mechanism favors one over the other. The three components become statistically independent, mimicking three independent scalars.[3] Also note that our result is similar to the case of the gradient of a scalar [45], in the sense that there are 6 independent normal random variables to describe the DM field at a given location and short time scales. 2.1.1 Equipartion and Ellipses In this subsection, we further justify our assumption of equipartition in the previous section. Equipartion and Vector Field Ellipses: There exist various production mechanisms where disparate amounts of longitudinal (spin-0) and transverse (spin-1) helicities are produced [20, 21, 23, 25]. That is, for every k, there could be different amounts of longitudinal and transverse components of Ψk [4]. However, owing to non-linear gravitational clustering, such disparity within the two sectors is expected to have disappeared by now within our local cosmic vicinity. With non-linear gravitational clustering, we expect virialization, leading to the equipartition of energy within all three degrees of freedom (dof). This would result in 2/3 of the total power being contained within the (two) transverse dof and the remaining 1/3 within the longitudinal ones. In this case, the vector field at each point (within a coherence region), which is formed out of a sum over a large number of Fourier modes, roughly traces out a randomly oriented ellipse (as opposed to oscillating along some fixed direction). This can be seen by noting that within time scales and length scales much smaller than the coherent ones, the spin current [31, 64] is negligible since it scales with the typical speed σ. Hence, the local spin density (given by s = A × A˙) is conserved, implying that the local field vector A can execute a two-dimensional sinusoidal motion in general, i.e. it sweeps an ellipse. See Fig. 1 for a visualization and a description of this evolution. Such elliptical motion is appropriately used in, for example, [65–67] In Appendix A, we discuss equipartition in greater detail, providing evidence for it via concrete halo-formation 3D simulations of the Schrodinger field Ψ. Random Linear Polarization: Some studies make the assumption of linear polarization; i.e. the vector field oscillates along a line in a fixed direction with this direction changing randomly every coherence time (see for example [40, 68–70]). However, as we argued above based on equipartition, an elliptical motion of the vector field is what one should expect. Nevertheless, we note that a preference for linear (circular) polarization could be generated by allowing for a non-gravitational attractive (repulsive) self-interaction [71– 73]. While these works argue for such a preference in isolated soliton-like configurations, whether a significant preference for linear (circular) polarization within each coherence patch can be achieved dynamically remains to be seen. Fixed Direction: There could exist a misalignment production mechanism for vectors where the entire observable Universe (or at least a large portion of it) has the vector field oscillating in a fixed direction [74, 75]. Such setups indeed lead to a fixed direction of oscillation of the vector field (apart from randomly oriented small perturbations). This would be distinct from the equipartition case we consider. However, there are difficulties associated with their production mechanisms [76–78]. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work; (2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work; (3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University; (4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Authors: Authors: (1) Dorian W. P. Amaral, Department of Physics and Astronomy, Rice University and These authors contributed approximately equally to this work; (2) Mudit Jain, Department of Physics and Astronomy, Rice University, Theoretical Particle Physics and Cosmology, King’s College London and These authors contributed approximately equally to this work; (3) Mustafa A. Amin, Department of Physics and Astronomy, Rice University; (4) Christopher Tunnell, Department of Physics and Astronomy, Rice University. Table of Links Abstract and 1 Introduction Abstract and 1 Introduction 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field 2.1 The Dark Photon Field 2.2 The Detector Signal 2.2 The Detector Signal 3 Statistical Analysis and 3.1 Signal Likelihood 3 Statistical Analysis and 3.1 Signal Likelihood 3.2 Projected Exclusions 3.2 Projected Exclusions 4 Application to Accelerometer Studies 4 Application to Accelerometer Studies 4.1 Recasting Generalised Limits onto B − L Dark Matter 4.1 Recasting Generalised Limits onto B − L Dark Matter 5 Future Directions 5 Future Directions 6 Conclusions, Acknowledgments, and References 6 Conclusions, Acknowledgments, and References A Equipartition between Longitudinal and Transverse Modes A Equipartition between Longitudinal and Transverse Modes B Derivation of Marginal Likelihood with Stochastic Field Amplitude B Derivation of Marginal Likelihood with Stochastic Field Amplitude C Covariance Matrix C Covariance Matrix D The Case of the Gradient of a Scalar D The Case of the Gradient of a Scalar 2 Calculating the Stochastic Wave Vector Dark Matter Signal 2.1 The Dark Photon Field With non-linear gravitational clustering, we expect an equipartition of longitudinal and transverse helicities of the plane waves in our vicinity, regardless of whether the early universe production mechanism favors one over the other. The three components become statistically independent, mimicking three independent scalars.[3] Also note that our result is similar to the case of the gradient of a scalar [45], in the sense that there are 6 independent normal random variables to describe the DM field at a given location and short time scales. 2.1.1 Equipartion and Ellipses 2.1.1 Equipartion and Ellipses In this subsection, we further justify our assumption of equipartition in the previous section. Equipartion and Vector Field Ellipses: There exist various production mechanisms where disparate amounts of longitudinal (spin-0) and transverse (spin-1) helicities are produced [20, 21, 23, 25]. That is, for every k, there could be different amounts of longitudinal and transverse components of Ψk [4]. However, owing to non-linear gravitational clustering, such disparity within the two sectors is expected to have disappeared by now within our local cosmic vicinity. With non-linear gravitational clustering, we expect virialization, leading to the equipartition of energy within all three degrees of freedom (dof). This would result in 2/3 of the total power being contained within the (two) transverse dof and the remaining 1/3 within the longitudinal ones. In this case, the vector field at each point (within a coherence region), which is formed out of a sum over a large number of Fourier modes, roughly traces out a randomly oriented ellipse (as opposed to oscillating along some fixed direction). This can be seen by noting that within time scales and length scales much smaller than the coherent ones, the spin current [31, 64] is negligible since it scales with the typical speed σ. Hence, the local spin density (given by s = A × A˙) is conserved, implying that the local field vector A can execute a two-dimensional sinusoidal motion in general, i.e. it sweeps an ellipse. See Fig. 1 for a visualization and a description of this evolution. Such elliptical motion is appropriately used in, for example, [65–67] In Appendix A, we discuss equipartition in greater detail, providing evidence for it via concrete halo-formation 3D simulations of the Schrodinger field Ψ. Random Linear Polarization: Some studies make the assumption of linear polarization; i.e. the vector field oscillates along a line in a fixed direction with this direction changing randomly every coherence time (see for example [40, 68–70]). However, as we argued above based on equipartition, an elliptical motion of the vector field is what one should expect. Nevertheless, we note that a preference for linear (circular) polarization could be generated by allowing for a non-gravitational attractive (repulsive) self-interaction [71– 73]. While these works argue for such a preference in isolated soliton-like configurations, whether a significant preference for linear (circular) polarization within each coherence patch can be achieved dynamically remains to be seen. Random Linear Polarization: Fixed Direction: There could exist a misalignment production mechanism for vectors where the entire observable Universe (or at least a large portion of it) has the vector field oscillating in a fixed direction [74, 75]. Such setups indeed lead to a fixed direction of oscillation of the vector field (apart from randomly oriented small perturbations). This would be distinct from the equipartition case we consider. However, there are difficulties associated with their production mechanisms [76–78]. Fixed Direction: This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

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