12 December 2019

Twitter is bringing back Election Labels to identify 2020 U.S. election candidates


With just under a year until U.S. Election Day, Twitter is bringing back its Election Labels, which provide information about political candidates — including what office they’re running for and their state and district number. The labels will also have a small ballot box icon to accompany this information. The feature was first launched during the 2018 U.S. midterms, where the labels were seen 100 million times per day by Twitter users in the week before Election Day.

In addition, 13% of U.S. election-related conversations on Twitter included a tweet with an Election Label, the company says.

Now the labels are making a return ahead of the 2020 U.S. elections.

The labels will appear on accounts of candidates who are running for the U.S. House of Representatives, U.S. Senate, or Governor in the 2020 election who have qualified for the general election ballot, says Twitter. And they will begin to appear on candidates’ Twitter accounts after they qualify, which will happen on a rolling basis as states have different caucus and election dates, the company notes. The first takes place on March 3rd.

To enable the feature, Twitter has again partnered with Ballotpedia, a civic nonprofit that publishes non-partisan information about federal, state and local politics. The organization will help Twitter to identify which candidates have qualified for the general election ballot so their accounts can be appropriately labeled.

The Election Label will appear on the profile page of a candidate’s Twitter account and on every tweet and retweet they post to their account, even when embedded on sites off of Twitter.

Ahead of this, Twitter today will also start to verify the campaign Twitter accounts of those who have qualified for primary elections for the U.S. House, Senate or Governor. This is different from how Twitter handled candidate verification during the 2018 midterms. Back then, it only verified candidates after they qualified for the general election ballot. This time around, Twitter says it will proactively verify the primary candidates.

This verification is the same checkmark other high-profile accounts receive — like those belonging to celebrities or other public figures. These verifications will start today and will continue on a rolling basis as states have different filing deadlines. Ballotpedia is also assisting on this effort as well, by helping Twitter identify the candidates.

Twitter, like other social platforms, had been heavily impacted by foreign interference with the U.S. 2016 presidential election. Last year, Twitter said that 1.4 million people had interacted with Russian trolls during the presidential campaign, which is more than double the 677,775 that Twitter originally believed had either seen, followed, or retweeted one of those accounts. These interference issues have been ongoing, as thousands of Twitter accounts spreading false information remained active in the weeks ahead of the U.S. midterms.

Bots continue today to infect the platform, in an effort to sway public opinion. For example, in April, Twitter removed over 5,000 bots with ties to a social media operation that previously promoted messages sympathetic to Saudi Arabia’s government. The bots had more recently been promoting the “Russiagate” hoax.

Disinformation efforts like this are not just impacting social platforms in the U.S. nor are they only associated with Russian bots. In a report released at the beginning of 2019, Twitter said it had banned more than 4,000 disinformation accounts originating in Russia, 3,300 from Iran, and more than 750 from Venezuela.

When Twitter first introduced the Election Labels for the U.S. midterms, it stressed how important it is for people using its platform to be able to identify the original sources and authentic information.

Today, Twitter’s system to label and verify politicians and candidates’ campaigns is now a part of a number of efforts Twitter has underway to make sure conversations taking place on its platform are authentic. The company says it will later release more tools to help better find quality news and have more informative conversations on Twitter.


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Amazon launches Audible Suno free app featuring short-stories in India


Amazon is having another go at expanding its reach to listeners in India. The company, which launched pay-to-use Audible in the country last year, today introduced a new service called Audible Suno that offers free access to “hundreds of hours of audio entertainment, enlightenment and learning.”

And it’s banking on major Indian celebrities to draw the listeners.

Audible Suno, which is exclusively available to users in India, features more than 60 original and exclusive episodes (of 20 to 60 minutes in length) in both Hindi and English languages. Audible, the world’s largest seller and producer of audio content, said Suno is aimed at filling the “idle time” listeners have each day during their commutes and performing other daily chores.

The company says Audible Suno, available to users through a dedicated Android app and via iOS Audible app, is also free of advertisements.

The launch of Audible Suno in India illustrates the commitment the company has in the country, said Audible founder and chief executive Don Katz. Amazon has invested more than $5.5 billion in its business in India to date. The company’s tentacles today reach a number of categories in the country including e-commerce, payments, online ticketing business, video and audio streaming, and VC deals.

“I’ve always been passionate about the transformative power of the spoken word, and I’m delighted to be able to offer this breadth of famous voices and culturally resonant genres with unlimited access, ad-free and free of charge,” said Katz.

Who are these famous voices you ask? Here’s the list: Amitabh Bachchan, Katrina Kaif, Karan Johar, Anil Kapoor, Farhan Akhtar, Mouni Roy, Anurag Kashyap, Neelesh Misra, Tabu, Nawazuddin Siddiqui, Diljit Dosanjh, Vir Das and Vicky Kaushal.

Audible Suno currently offers shows in a range of genres, including horror (Kaali Awaazein), romance and relationships (Matrimonial Anonymous and Piya Milan Chowk), suspense (Thriller Factory), and comedy series (The Unexperts by Abish Mathew). Non-fiction series include interviews with some of the country’s biggest stars, and socially relevant subjects such as mental health, sex education and the rights of the LGBTQI+ community.


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Yubo raises $12.3 million for its social app for teens


French startup Yubo has raised a $12.3 million funding round led by Iris Capital and Idinvest Partners. Existing investors Alven, Sweet Capital and Village Global are also participating. The startup has managed to attract 25 million users over the years — there are currently tens of thousands of people signing up to the platform every day.

Yubo is building a social media app for young people under 25 with one focus in particular on helping teenagers meeting new people and creating friendships. Compared to the most popular social media apps out there, Yubo isn’t focused on likes and followers.

Instead, the app helps you build your own tiny little community of friends. Yubo wants to become a familiar place where you belong, even if high school sucks for instance.

More details in my previous profile of the company:

In addition to meeting new people, you can start conversations and create live video streams to hang out together. Each stream represents a micro-community of people interacting through both video and a live chat.

Since 2015, Yubo users have sent each other 10 billion messages and started 30 million live video streams. Overall, the user base has generated 2 billion friendships.

Soon, users will be able to turn on screensharing to show something on their phones. And at some point in 2020, Yubo should release Yubo Web in order to expand Yubo beyond your smartphone and enable new use cases, such as video game live streaming.

With today’s funding round, the company wants to attract users in new markets. Yubo is mostly active in the U.S., Canada, the U.K., Nordic countries, Australia and France. Up next, the startup is going to focus on Japan and Brazil. The company plans to hire 35 new people.

When it comes to a business model, the company started monetizing its app in October 2018 with in-app purchases to unlock new features. In 2019, the startup has generated $10 million in revenue.

Yubo will also use this funding round to improve safety. It’s a never-ending process, especially when there are young people using your platform. The company already partners with Yoti for age verification. Users will soon be able to create a blocklist of certain words to customize their experience.

In addition to continuous work on flagging tools and live-stream moderation algorithms in order to detect inappropriate content, the company will also increase the size of its moderation team. The company has also put together a safety board with Alex Holmes, Annie Mullins, Travis Bright, Mick Moran, Dr. Richard Graham and Anne Collier.


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A guide to collaborative leadership | Lorna Davis

A guide to collaborative leadership | Lorna Davis

What's the difference between heroes and leaders? In this insightful talk, Lorna Davis explains how our idolization of heroes is holding us back from solving big problems -- and shows why we need "radical interdependence" to make real change happen.

Click the above link to download the TED talk.

Facebook Messenger adds Star Wars-themed features and AR effects


Star Wars has come to Facebook’s Messenger app. Facebook today announced a new set of Star Wars-themed features for Messenger users, including a chat theme, reactions, stickers, and AR effects. The features were developed in partnership with Disney to help promote the upcoming film, “Star Wars: The Rise of Skywalker,” which premieres nationwide on December 20.

Both the stickers and the reactions allow users to express themselves using characters from both sides of The Force, says Facebook. Disney also helped to create a set of limited-edition AR effects which can be used both while taking photos and selfies or when you’re on video calls.

One, the Lightspeed Effect, gives the appearance of jumping into hyperspace. Another, the Cockpit Effect, lets you see yourself as a member of the Resistance, traveling across the galaxy in Poe Dameron’s X-Wing. The Dark vs Light Effect lets you choose your side of the Force.

There’s also a Star Wars chat theme you can enable from the Messenger thread settings. (You access the Settings by tapping the thread’s name — typically the name or names of those you’re chatting with at the top of the screen, unless you or someone else has already renamed the chat.)

This isn’t the first time Disney has partnered with a major tech company on a big marketing push around the Star Wars franchise. In 2015, Disney teamed up with Google to built out a new tool that let you theme its suite of apps, including Gmail, YouTube, Google Maps Chrome and others with either a Light Side or Dark Side effect. Facebook that year also let users change their profile photo to a Star Wars-themed pic where they posed with a red Dark Side cross-guard lightsaber or a Light Side blue one.

And in 2017, Google launched an AR Stickers app with a set of licensed characters from Star Wars to promote The Last Jedi. Apple got on board, too, with an updated version of its Clips app with a set of new “Selfie Scenes,” including those for the Millennium Falcon and Mega-Destroyer, also from Star Wars: The Last Jedi.

The sorts of collaborations benefit both parties. In the case of this new Messenger partnership, Disney gets to market its new movie to Messenger’s over one billion users. Meanwhile, Facebook gains increased usage and engagement for its popular Messenger app in a competitive market, where AR effects alone can be a key selling point for attracting users.

The new Star Wars features are rolling out today, December 12, to Messenger.

 


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Robinhood lets you invest as little as 1 cent in any stock


One share of Amazon stock costs over $1700, locking out less wealthy investors. So to continue its quest to democratize stock trading, Robinhood is launching fractional share trading this week. This lets you buy 0.000001 shares, rounded to the nearest penny, or just $1 of any stock with zero fee.

The ability to buy by millionth of a share lets Robinhood undercut Square Cash’s recently announced fractional share trading, which sets a $1 minimum for investment. Robinhood users can sign up here for early access to fractional share trading. “One of our core values is participation is power” says Robinhood co-CEO Vlad Tenev. “Everything we do is rooted in this. We believe that fractional shares have the potential to open up investing for even more people.”

Fractional share trading ensures no one need be turned away, and Robinhood can keep growing its user base of 10 million with its war chest of $910 million in funding. As incumbent brokerages like Charles Schwab and E*Trade move to copy Robinhood’s free stock trading, the startup has to stay ahead in inclusive financial tools. In this case, though, it’s trying to keep up since Schwab, Square, Stash, and SoFi all launched fractional shares this year. Betterment has actually offered this since 2010.

Robinhood has a bunch of other new features aimed at diversifying its offering for the not-yet-rich. Today its Cash Management feature it announced in October is rolling out to its first users on 800,000 person wait list, offering them 1.8% APY interest on cash in their Robinhood balance plus a Mastercard debit card for spending money or pulling it out of a wide network of ATMs. The feature is effectively a scaled-back relaunch of the botched debut of 3% APY Robinhood Checking a year ago which was scuttled since the startup failed to secure the proper insurance it now has for Cash Management.

Additionally, Robinhood is launching two more widely requested features early next year. Dividend Reinvestment Plan (DRIIP) will automatically reinvest cash dividends Robinhood users receive into stocks or ETFS. Recurring Investments will let users schedule daily, weekly, bi-weekly, or monthly investments into stocks. With all this, Crypto trading, and  Robinhood is evolving into a full financial services suite that will be much harder for competitors to copy.

Robinhood Debit Card

How Robinhood Fractional Shares Work

“We believe that if you want to invest, it shouldn’t matter how much money you have. With fractional shares, we’re opening up a whole universe of stocks and funds including Amazon, Apple, Disney, Berkshire Hathaway, and thousands of others” Robinhood product manager Abhishek Fatehpuria tells me.

Users will be able to place real-time fractional share orders in dollar amounts as low as $1 or share amounts as low as 0.000001 shares rounded to the penny during market hours. Stocks worth over $1 per share with a market capitalization above $25 million are eligible, with 4000 different stocks and ETFs available for commission-free, real-time fractional trading.

“We believe that participation is power. Since day one, we’ve focused on breaking down barriers like trade commissions and account minimums to help people participate in the financial system” says Fatehpuria. “We have a unique user base — half our customers tell us they’re first time investors, and the median age of a Robinhood customer is 30. This means we have a unique opportunity to expand access to the markets for this new generation.”

Robinhood is racing to corner the freemium investment tool market before other startups and finance giants can catch up. It opened a waitlist for its UK launch next year which will be its first international market. But in just the past month, Alpaca raised $6 million for an API that lets anyone build a stock brokerage app, and Atom Finance raised $10.6 million for its free investment research tool that could compete with Robinhood’s in-app feature. Meanwhile, Robinhood suffered an embarrassing bug letting users borrow more money than allowed.

The move fast and break things mentality triggers new dangers when introduced to finance. Robinhood must resist the urge to rush as it spreads itself across more products in pursuit of a leveler investment playing field.


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Chatbots spotlight machine learning’s trillion-dollar potential


The global industry potential of artificial intelligence is well-documented, yet the vision of this AI future is uncertain.

AI and automation trends are generating significant debate among economists and governments, particularly around employment impact and uncertain social outcomes. The mainstream attention is warranted. According to PwC, AI “could contribute up to $15.7 trillion to the global economy in 2030, more than the current output of China and India combined.”

AI is at a crossroads, and its long-term outlook is still hotly debated. Despite social media giants, automotive companies and numerous other industries investing hundreds of billions of dollars in AI, many automation technologies are not yet directly generating revenue and instead are forecasted to become profitable in the coming decades. This creates additional uncertainty of AI’s true market potential. The realistic potential value of AI is unknown, yet, as the technology advances, the ultimate impact could be of great consequence to virtually every economy.

There are many reasons to view AI’s future from an optimistic lens, however: chatbots provide significant evidence for AI’s positive impact on both business growth and employment markets. Today, chatbots are increasingly capable of mimicking human interactions and conversations to assist business-to-business, business-to-consumer, business-to-government, advertising audiences and other diverse groups. The evolution of the cognitive computer science behind conversational chatbots is perhaps one of the best examples of AI technologies driving revenue. Further, chatbot technology shows some of the greatest promise for augmenting, rather than replacing human workers.

AI is driving value while augmenting human workers

Chatbots are delivering real revenue today for some of the world’s leading financial services (Bank of America), retail (Levi’s), and technology companies (Zendesk). We’re seeing more consumers taking the next step in a transaction or even making a purchase decision based off conversations with chatbots. Beyond driving sales, chatbots have numerous applications to a wide range of organizations. Nonprofits, NGOs, and even political campaigns find value in deploying chatbots to help handle the influx of inquiries from stakeholders and relevant audiences.

Rather than these chatbots replacing human workers, organizations are finding chatbots to be a helpful and value-creating opportunity that frees employees to focus on more strategic tasks. Apple’s Siri, Amazon Alexa and Microsoft Cortana aren’t replacing executive assistants today, but these technologies are all capable of supporting the executive assistant function in the workplace.

Gartner predicts AI augmentation, defined as a “human-centered partnership model of people and AI working together to enhance cognitive performance,” could generate $2.9 trillion of business value by 2021. Many industries see potential for chatbots to augment functions like sales, customer support and IT, enabling workers to create value in more strategic ways. Bain & Company finds chatbots to be among the most notable examples of artificial intelligence and automation in practice: “Companies use AI applications to understand industry trends, manage their workforce, address problems, power chatbots and personalize content to enable self-service.”

Clearly, the implications of scaled, human-like engagement are stunning in their capacity to carry out tasks. A chatbot’s ability to simultaneously hold tens of thousands of conversations — pulling from many millions of data points — is comparable to what a human customer service rep could accomplish in more than 1,000 years of nonstop work. Scaling customer service via AI allows service professionals to focus on big picture and more complex issues, and it provides rich data on customer interactions. We anticipate seeing more companies look to build better customer service experiences through chatbots, as Google and Salesforce announced in April.

The transformative impact of chatbots across industries

From our research and work with leading global companies, it’s clear that enterprises are finding that chatbots bring about tremendous value while supporting both people employment and long-term business growth opportunities today. Ultimately, chatbots are on track to showcase some of the most optimistic examples of AI augmentation. Consider three examples:


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Waymo buys Latent Logic, drives deeper into simulation and Europe


Waymo has acquired Latent Logic, a UK company that spun out of Oxford University’s computer science department, as the autonomous vehicle company seeks to beef up its simulation technology.

The acquisition also marks the launch of Waymo’s first European engineering hub will be in Oxford, UK. This likely won’t be the end of Waymo’s expansion and investment in Europe and the UK. The former Google self-driving project that is now an Alphabet business said it will continue to look for opportunities to grow the team in the UK and Europe.

Earlier this year, Waymo locked in an exclusive partnership with Renault and Nissan to research how commercial autonomous vehicles might work for passengers and packages in France and Japan. In October, Waymo said that its working with Renault to study the possibility of establishing an autonomous transportation route in Paris.

Waymo has made simulation a one of the pillars of its autonomous vehicle development program. But Latent Logic could help Waymo make its simulation more realistic by using a form of machine learning called imitation learning.

Imitation learning models human behavior of motorists, cyclists and pedestrians. The idea is that by modeling the mistakes and imperfect driving of humans, the simulation will become more realistic and theoretically improve Waymo’s behavior prediction and planning.

Waymo isn’t sharing financial details of the acquistion. But it appears that the two founders Shimon Whiteson and João Messia, CEO Kirsty Lloyd-Jukes and key members of the engineering and technical team will join Waymo. The Latent Logic team will remain in Oxford.

“By joining Waymo, we are taking a big leap towards realizing our ambition of safe, self-driving vehicles,” said Latent Logic co-founder and chief scientist Shimon Whiteson. “In just two years, we have made significant progress in using imitation learning to simulate real human behaviors on the road. I’m excited by what we can now achieve in combining this expertise with the talent, resources and progress Waymo have already made in self-driving technology.”

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Interpreter, Google’s real-time translator, comes to mobile


After rolling out on smart speakers and displays earlier this year, Google’s interpreter real-time translation mode finally landing on mobile. A far more handy application for such functionality, the feature arrives on both Android and iOS handsets globally, starting today.

The feature works in tandem with Assistant. Say something like, “Hey Google, be my German translator” or “Hey Google, help me speak Thai,” and the feature kicks in, offering up a real-time translated transcript and audio. The feature also offers some Smart Replies a la Gmail, to help keep the conversation going.

The feature is now available in 44 languages (full list here), up from the 29 available on the smart displays/speakers. It’s integrated directly into the Google Assistant app, negating the need to download an additional translation app. Between this and Lens, Google’s apps have quickly become a necessary part of traveling abroad.


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Atom Finance’s free Bloomberg Terminal rival raises $12M


If you want to win on Wall Street, Yahoo Finance is insufficient but Bloomberg Terminal costs a whopping $24,000 per year. That’s why Atom Finance built a free tool designed to democratize access to professional investor research. If Robinhood made it cost $0 to trade stocks, Atom Finance makes it cost $0 to know which to buy.

Today Atom launches its mobile app with access to its financial modeling, portfolio tracking, news analysis, benchmarking, and discussion tools. It’s the consumerization of finance, similar to what we’ve seen in enterprise SAAS. “Investment research tools are too important to the financial well-being of consumers to lack the same cycles of product innovation and accessibility that we have experienced in other verticals” CEO Eric Shoykhet tells me.

In its first press interview, Atom Finance today revealed to TechCrunch that it’s raised a $10.6 million Series A led by General Catalyst to build on its quiet $1.9 million seed round. The cash will help the startup eventually monetize by launching premium tiers with even more hardcore research tools.

Atom Finance already has 100,000 users and $400 million in assets it’s helping steer since soft-launching in June. “Atom fundamentally changes the game for how financial news media and reporting is consumed. I could not live without it” says The Twenty Minute VC podcast founder Harry Stebbings.

Individual investors are already at a disadvantage compared to big firms equipped with artificial intelligence, the priciest research, and legions of traders glued to the markets. Yet it’s becoming increasingly clear that investing is critical to long-term financial mobility, especially in an age of rampant student debt and automation threatening employment.

“Our mission is two fold” Shoykhet says. “To modernize investment research tools through an intuitive platform that’s easily accessible across all devices, while democratizing access to institutional-quality investing tools that were once only available to Wall Street professionals.”

Leveling The Trading Floor

Shoykhet saw the gap between amateur and expert research platforms first hand as an investor at Blackstone and Governors Lane. Yet even the supposedly best-in-class software was lacking the usability we’ve come to expect from consumer mobile apps. Atom Finance claims that “for example, Bloomberg hasn’t made a significant change to its central product offering since 1982.”

Atom Finance Team

So a year ago, Shoykhet founded Atom Finance in Brooklyn to fill the void. Its web, iOS, and Android apps offer five products that combine to guide users’ investing decisions without drowning them in complexity:

  • Sandbox – Instant financial modeling with pre-populated consensus projections that automatically update and are recalculated over time
  • Portfolio – Track your linked investment accounts to monitor overarching stats, real-time profit and loss statements, and diversification
  • X-Ray – A financial research search engine for compiling news, SEC filings, transcripts, and analysis
  • Compare – Benchmarking tables for comparing companies and sectors
  • Collaborate – Discussion boards and group chat for sharing insights with fellow investors

“Our Sandbox feature allows users to create simple financial models directly within our platform, without having to export data to a spreadsheet” Shoykhet says. “This saves our users time and prevents them from having to manually refresh the inputs to their model when there is new information.”

Shoykhet positions Atom Finance in the middle of the market, saying “Existing solutions are either too rudimentary for rigorous analysis (Yahoo Finance, Google Finance) or too expensive for individual investors (Bloomberg, CapIQ, Factset).”

With both its free and forthcoming paid tiers, Atom hopes to undercut Sentieo, a more AI-focused financial research platform that charges $500 to $1000 per month and raised $19 million a year ago. Cheaper tools like BamSEC and WallMine are often limited to just pulling in earnings transcripts and filings. Robinhood has its own in-app research tools, which could make it a looming competitor or a potential acquirer for Atom Finance.

Shoykhet admits his startup will face stiff competition from well-entrenched tools like Bloomberg. “Incumbent solutions have significant brand equity with our target market, and especially with professional investors. We will have to continue iterating and deliver an unmatched user experience to gain the trust/loyalty of these users” he says. Additionally, Atom Finance’s access to users’ sensitive data mean flawless privacy, security, and accuracy will be essential.

The $12.5 million from General Catalyst, Greenoaks, Global Founders Capital, Untitled Investments, Day One Ventures, and a slew of angels gives Atom runway to rev up its freemium model.  Robinhood has found great success converting unpaid users to its subscription tier where they can borrow money to trade. By similarly starting out free, Atom’s 8-person team hailing from SoFi, Silver Lake, Blackstone, and Citi could build a giant funnel to feed its premium tiers.

Fintech can feel dry and ruthlessly capitalistic at times. But Shoykhet insists he’s in it to equip a new generation with methods of wealth creation. “I think we’ve gone long enough without seeing real innovation in this space. We can’t be complacent with something so important. It’s crucial that we democratize access to these tools and educate consumers . . . to improve their investment well-being.”


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Recover Deleted Files and Manage NTFS Drives With This Mac Software Bundle


Most of the time, computers do a great job of keeping our data safe and organized. But just occasionally, files get lost or become inaccessible. The iBoysoft Data Recovery + NTFS for Mac Bundle helps you keep things running smoothly, with two great apps for file management. This dynamic duo includes a powerful data recovery app and a lightweight NTFS driver, meaning you can access Windows-formatted drives. You can pick up the bundle now for $19 at MakeUseOf Deals.

Recovery and Access

Some files are just too precious to lose. If you ever accidentally delete your family photos, or your tax records get corrupted, iBoysoft Data Recovery will save the day.

This well-reviewed app allows you to recover any file in three easy steps. You simply select the drive, run a scan, and choose what you want to recover. iBoysoft can recover photos, videos, documents, emails, music files, and even entire partitions.

In terms of drives, the software works with inaccessible/unreadable external hard drives, USB flash drives, SD cards, memory cards, and your Macintosh.

The other half of this drive is iBoysoft NTFS for Mac. This lightweight driver lets you read, write, delete, and move files that are stored on Windows-formatted drives.

Two Apps for $19

These apps are worth $99.90 in total, but you can grab the bundle now for $19 — that’s 80% off the MSRP.

Read the full article: Recover Deleted Files and Manage NTFS Drives With This Mac Software Bundle


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7 Tips to Save Money on PC Repairs


pc-repair

You don’t have to pay for expensive technical assistance to repair your PC. Most repairs are simple and can be completed in a matter of minutes.

Here are nine tips for making simple PC repairs and save money on computer shop repair prices.

But I Don’t Know How to Repair a PC!

Before the home PC revolution of the 1990s, the techiest thing I had ever done was plug in a joystick. I didn’t even own a PC until 2001, when I was 25.

Years later, while I’m no Linux guru or Microsoft Visual Studio wizard, I can handle computer hardware side of computers. I learned how to repair computer hardware, and I’m confident you can too.

Repairing your own PC means you can save money. PC repair shops charge for parts and labor. If you can get the parts cheaply, why not learn how to fit them yourself?

Don’t think you can? Think again: the secret is in understanding how the various parts of the PC work together. While not everything is replaceable, the disk drive, power supply, RAM, processor, and motherboard can all be repaired or replaced.

Use these seven PC repair tips to save money, time waiting, and to expand your skillset.

1. Hard Disk Recovery & Replacement

The hard disk drive is arguably the most common PC part to require repair. Failure might be due to dying hardware or malware.

Either way, you will probably have a large amount of data that needs recovering.  so that you can continue to use it. Our guide to recovering data from a dead hard disk drive (HDD) is the place to start.

When you have successfully recovered your data and backed it up to disc, you’ll need a new hard disk drive. Amazon is a great place to find affordable HDDs.

Installing a new drive—like most PC components—is straightforward and can usually be done with the minimum of fuss. Before replacing a drive, check these tips for installing a new HDD.

2. Testing and Replacing Your Power Supply

A common problem in older computers is a defective power supply unit (PSU).

General maintenance and housekeeping can keep your PC free of clogged up dust. However, something will eventually cause your power supply unit to go rogue.

But what can you do, besides trekking to the nearest store or spending hours at home waiting for a delivery? Well, if you need to get up and running ASAP, you could always try a PSU from an old computer. This might be one you have stored in the basement, loft, or garage.

Note that this should only be a short-term fix, however. Your best bet is a new PSU, making sure it is perfect for your PC and how you use it.

3. Replacing and Upgrading RAM Modules

Not all RAM is created equally. Cheaper RAM modules tend to be slower and less reliable. Meanwhile multiple sticks of RAM should be identical. Mixing and matching is a bad idea, as the slowest of the group determines the maximum performance.

Should you need to upgrade your RAM, you’ll need to take care selecting the right module for your system. The combination of motherboard and processor (CPU) make this a balancing act—fortunately it’s simple to find the right combination.

A good way to check the best RAM modules for your system is to use an online checking tool. RAM manufacturers Crucial offer two RAM checking tools on their website. One of these lets you browse for your PC model, while the other is downloadable and scans your system.

Within a few minutes you should know exactly which RAM modules to buy and how much to spend. With the RAM ordered replacing a module is as simple as inserting a disk.

4. Simple PC Display Issues Repaired

Display issues on your desktop PC could have many causes. Perhaps the monitor is suspect; there could be a display driver issue; the HDMI cable might be dud.

All of these can be easily checked and resolved. But what if the problem is hardware based and the display is working perfectly?

For PCs equipped with a discrete graphics card (that is, a GPU installed in an expansion slot), replacement is likely. However, it is worth checking first that the device is correctly powered and isn’t overheating.

Overheating issues can often be resolved by improving airflow or adding a new fan to your PC case. Don’t worry if the problems eventually result in you replacing the GPU. It’s much like replacing or adding RAM modules, with the same antistatic precautions.

5. When Your Computer Needs a New CPU

Install a CPU in your PC

One of the most crushing disappointments when troubleshooting a PC is the discovery that your CPU needs replacing. Buying a new CPU can be difficult, so check our guide to dual core and quad core differences for help.

The anticipation of a new processor and the speed benefits your PC might gain is always good. The knowledge that you’ve saved upwards of $50 for the pleasure of fitting the CPU yourself is also pretty amazing.

6. Problems With Your Optical Drive? Try This

You’ve perhaps noticed that the components with the most moving parts are the ones that can cause the most problems. Hard disk drives can suffer mechanical failure, as can CD, DVD, and Blu-ray drives—together known as optical drives.

One way you can overcome a failing optical drive is to use an old laptop drive as a temporary replacement. If you find that you must replace the device, don’t worry. It’s an almost identical procedure to fitting a hard disk drive.

7. Repairing and Replacing Your Motherboard

Mini ITX motherboard

Of all the problems you might experience when troubleshooting your PC, motherboard issues are perhaps the toughest to deal with.

It isn’t just the fact that every component must be stripped out and disconnected before you safely remove the motherboard. One wrong move with a screwdriver or even when putting the motherboard in the case and you’ll be buying a replacement.

There are, of course, some simple motherboard-related issues. BIOS problems are often related to jumpers or the motherboard battery and typically resolved by referring to the motherboard manual.

Easily Make Simple PC Repairs and Save Money

Perhaps we’re making it harder for the tech support industry to earn a living, but we’d rather help develop a new generation of self-sufficient individuals who can repair their kit without the fear of 1s and 0s clouding their judgment.

Remember, no one is born with these skills. They must be learned, which means anyone can do it. If you feel you need assistance from a specialist, find a friend or relative who can be ready to help. Only pay for expensive tech support if there is no other option.

Looking for more affordable computing tips? Here’s how to save money buying used games online.

Read the full article: 7 Tips to Save Money on PC Repairs


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‘Disney Plus’ was the #1 U.S. Google search term in 2019


Google today released its annual “Year in Search” data that takes a look back at some of the biggest searches of 2019. Specifically, Google looked at the biggest trends — meaning, search terms that saw the largest spikes in traffic over a sustained period in 2019 compared to 2018. In the U.S., Disney’s new streaming service “Disney Plus” was the biggest search trend of 2019, followed by Cameron Boyce, Nipsey Hussle, Hurricane Dorian, Antonio Brown, Luke Perry, Avengers: Endgame, Game of Thrones, iPhone 11, and Jussie Smollet.

“Game of Thrones” was also the biggest U.S. TV show search trend of the year, followed by Netflix’s “Stranger Things” and “When They See Us,” then HBO’s “Chernobyl,” and Disney Plus’s “The Mandalorian.”

On the global stage, Apple’s iPhone 11 was the fifth biggest trend of the year, one ahead of Game of Thrones (#6), but behind searches for “India vs South Africa,” which ranked No. 1. The rest of the list included (in order): Cameron Boyce (#2), Copa America (#3), Bangladesh vs India (#4), Avengers: Endgame (#7), Joker (#8), Notre Dame (#9), and ICC Cricket World Cup (#10).

Tech companies’ influence on Google’s Top Trends could also be found in the music category, where “Old Town Road” was the top trending Song globally and in the U.S. in 2019. The Lil Nas X hit song went viral on TikTok this year after the rapper himself uploaded it to the platform back in December 2018.

In addition to topping Google’s list, Lil Nas X was also the No. 1 artist on TikTok according to its own year-end round-up.

Elsewhere, online and tech-influenced trends could be found under the “What is…?” category in Google’s top U.S. search trends. For example, the meme “Storm Area 51” which grew out of of a viral Facebook joke that turned into a real-world event led many this year to search “What is Area 51?”

No. 2 was “What is a VSCO girl?” referring to the latest teen trend and meme whose name comes from the hipper-than-Instagram photo-editing app, VSCO. The VSCO girl dresses in oversized tees, Birkenstocks, wears her hair in a messy bun, and adorns herself with accessories like scrunchies, Burt’s Bees lip balm, puka shell chokers, and carries around a Hydro Flask water bottle.

Also on the “What is…?” list were “momo” as in the “Momo Challenge,” (an artistic sculpture turned viral hoax) and “What is a boomer?,” referencing the latest teen insult for old people, “OK boomer.” The latter also became a huge TikTok meme.

Various online cultures influenced Google’s top U.S. outfit trends, too, including the No. 1 outfit idea of Egirl, a popular demographic found on TikTok that’s a sort of emo subculture (or perhaps an emo-anime-goth variation), followed by Eboy, Soft girl (another TikTok subculture, this time with a hyper-cute aesthetic), and finally Biker shorts and VSCO girl. (If you don’t know which one you are, don’t worry — there’s a BuzzFeed quiz for that, of course.)

Google’s top trends are mainly a reflection of pop culture for the year, Google did take a longer look back this year with its “Decade in Search” retrospective, where it highlights the music, movies and people who influenced culture over the past 10 years.

The company put together a busy visualization of the decade in music through Year in Search, for example.

Made with Flourish

It also points to some of the people who trended over the course of the decade, including Justin Bieber, Betty White, Lebron James, as well as long-lasting TV and movie trends, including “Toy Story”, “Iron Man,” and “The Walking Dead.”

The full list of Google’s Global Top Trends, which can be filtered by country, is here.


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Many smart home device makers still won’t say if they give your data to the government


A year ago, we asked some of the most prominent smart home device makers if they have given customer data to governments. The results were mixed.

The big three smart home device makers — Amazon, Facebook and Google (which includes Nest) — all disclosed in their transparency reports if and when governments demand customer data. Apple said it didn’t need a report, as the data it collects was anonymized.

As for the rest, none had published their government data-demand figures.

In the year that’s past, the smart home market has grown rapidly, but the remaining device makers have made little to no progress on disclosing their figures. And in some cases, it got worse.

Smart home and other internet-connected devices may be convenient and accessible, but they collect vast amounts of information on you and your home. Smart locks know when someone enters your house, and smart doorbells can capture their face. Smart TVs know which programs you watch and some smart speakers know what you’re interested in. Many smart devices collect data when they’re not in use — and some collect data points you may not even think about, like your wireless network information, for example — and send them back to the manufacturers, ostensibly to make the gadgets — and your home — smarter.

Because the data is stored in the cloud by the devices manufacturers, law enforcement and government agencies can demand those companies turn over that data to solve crimes.

But as the amount of data collection increases, companies are not being transparent about the data demands they receive. All we have are anecdotal reports — and there are plenty: Police obtained Amazon Echo data to help solve a murder; Fitbit turned over data that was used to charge a man with murder; Samsung helped catch a sex predator who watched child abuse imagery; Nest gave up surveillance footage to help jail gang members; and recent reporting on Amazon-owned Ring shows close links between the smart home device maker and law enforcement.

Here’s what we found.

Smart lock and doorbell maker August gave the exact same statement as last year, that it “does not currently have a transparency report and we have never received any National Security Letters or orders for user content or non-content information under the Foreign Intelligence Surveillance Act (FISA).” But August spokesperson Stephanie Ng would not comment on the number of non-national security requests — subpoenas, warrants and court orders — that the company has received, only that it complies with “all laws” when it receives a legal demand.

Roomba maker iRobot said, as it did last year, that it has “not received” any government demands for data. “iRobot does not plan to issue a transparency report at this time,” but it may consider publishing a report “should iRobot receive a government request for customer data.”

Arlo, a former Netgear smart home division that spun out in 2018, did not respond to a request for comment. Netgear, which still has some smart home technology, said it does “not publicly disclose a transparency report.”

Amazon-owned Ring, whose cooperation with law enforcement has drawn ire from lawmakers and faced questions over its ability to protect users’ privacy, said last year it planned to release a transparency report in the future, but did not say when. This time around, Ring spokesperson Yassi Shahmiri would not comment and stopped responding to repeated follow-up emails.

Honeywell spokesperson Megan McGovern would not comment and referred questions to Resideo, the smart home division Honeywell spun out a year ago. Resideo’s Bruce Anderson did not comment.

And just as last year, Samsung, a maker of smart devices and internet-connected televisions and other appliances, also did not respond to a request for comment.

On the whole, the companies’ responses were largely the same as last year.

But smart switch and sensor maker Ecobee, which last year promised to publish a transparency report “at the end of 2018,” did not follow through with its promise. When we asked why, Ecobee spokesperson Kristen Johnson did not respond to repeated requests for comment.

Based on the best available data, August, iRobot, Ring and the rest of the smart home device makers have hundreds of millions of users and customers around the world, with the potential to give governments vast troves of data — and users and customers are none the wiser.

Transparency reports may not be perfect, and some are less transparent than others. But if big companies — even after bruising headlines and claims of co-operation with surveillance states — disclose their figures, there’s little excuse for the smaller companies.

This time around, some companies fared better than their rivals. But for anyone mindful of their privacy, you can — and should — expect better.


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Timeline of the Universe


Timeline of the Universe

Fairness Indicators: Scalable Infrastructure for Fair ML Systems




While industry and academia continue to explore the benefits of using machine learning (ML) to make better products and tackle important problems, algorithms and the datasets on which they are trained also have the ability to reflect or reinforce unfair biases. For example, consistently flagging non-toxic text comments from certain groups as “spam” or “high toxicity” in a moderation system leads to exclusion of those groups from conversation.

In 2018, we shared how Google uses AI to make products more useful, highlighting AI principles that will guide our work moving forward. The second principle, “Avoid creating or reinforcing unfair bias,” outlines our commitment to reduce unjust biases and minimize their impacts on people.

As part of this commitment, at TensorFlow World, we recently released a beta version of Fairness Indicators, a suite of tools that enable regular computation and visualization of fairness metrics for binary and multi-class classification, helping teams take a first step towards identifying unjust impacts. Fairness Indicators can be used to generate metrics for transparency reporting, such as those used for model cards, to help developers make better decisions about how to deploy models responsibly. Because fairness concerns and evaluations differ case by case, we also include in this release an interactive case study with Jigsaw’s Unintended Bias in Toxicity dataset to illustrate how Fairness Indicators can be used to detect and remediate bias in a production machine learning (ML) model, depending on the context in which it is deployed. Fairness Indicators is now available in beta for you to try for your own use cases.

What is ML Fairness?
Bias can manifest in any part of a typical machine learning pipeline, from an unrepresentative dataset, to learned model representations, to the way in which the results are presented to the user. Errors that result from this bias can disproportionately impact some users more than others.

To detect this unequal impact, evaluation over individual slices, or groups of users, is crucial as overall metrics can obscure poor performance for certain groups. These groups may include, but are not limited to, those defined by sensitive characteristics such as race, ethnicity, gender, nationality, income, sexual orientation, ability, and religious belief. However, it is also important to keep in mind that fairness cannot be achieved solely through metrics and measurement; high performance, even across slices, does not necessarily prove that a system is fair. Rather, evaluation should be viewed as one of the first ways, especially for classification models, to identify gaps in performance.

The Fairness Indicators Suite of Tools
The Fairness Indicators tool suite enables computation and visualization of commonly-identified fairness metrics for classification models, such as false positive rate and false negative rate, making it easy to compare performance across slices or to a baseline slice. The tool computes confidence intervals, which can surface statistically significant disparities, and performs evaluation over multiple thresholds. In the UI, it is possible to toggle the baseline slice and investigate the performance of various other metrics. The user can also add their own metrics for visualization, specific to their use case.

Furthermore, Fairness Indicators is integrated with the What-If Tool (WIT) — clicking on a bar in the Fairness Indicators graph will load those specific data points into the the WIT widget for further inspection, comparison, and counterfactual analysis. This is particularly useful for large datasets, where Fairness Indicators can be used to identify problematic slices before the WIT is used for a deeper analysis.
Using Fairness Indicators to visualize metrics for fairness evaluation.
Clicking on a slice in Fairness Indicators will load all the data points in that slice inside the What-If Tool widget. In this case, all data points with the “female” label are shown.
The Fairness Indicators beta launch includes the following:
How To Use Fairness Indicators in Models Today
Fairness Indicators is built on top of TensorFlow Model Analysis, a component of TensorFlow Extended (TFX) that can be used to investigate and visualize model performance. Based on the specific ML workflow, Fairness Indicators can be incorporated into a system in one of the following ways:
If using TensorFlow models and tools, such as TFX:
  • Access Fairness Indicators as part of the Evaluator component in TFX
  • Access Fairness Indicators in TensorBoard when evaluating other real-time metrics
If not using existing TensorFlow tools:
  • Download the Fairness Indicators pip package, and use Tensorflow Model Analysis as a standalone tool
For non-TensorFlow models:
Fairness Indicators Case Study
We created a case study and introductory video that illustrates how Fairness Indicators can be used with a combination of tools to detect and mitigate bias in a model trained on Jigsaw’s Unintended Bias in Toxicity dataset. The dataset was developed by Conversation AI, a team within Jigsaw that works to train ML models to protect voices in conversation. Models are trained to predict whether text comments are likely to be abusive along a variety of dimensions including toxicity, insult, and sexual explicitness.

The primary use case for models such as these is content moderation. If a model penalizes certain types of messages in a systematic way (e.g., often marks comments as toxic when they are not, leading to a high false positive rate), those voices will be silenced. In the case study, we investigated false positive rate on subgroups sliced by gender identity keywords that are present in the dataset, using a combination of tools (Fairness Indicators, TFDV, and WIT) to detect, diagnose, and take steps toward remediating the underlying problem.

What’s next?
Fairness Indicators is only the first step. We plan to expand vertically by enabling more supported metrics, such as metrics that enable you to evaluate classifiers without thresholds, and horizontally by creating remediation libraries that utilize methods, such as active learning and min-diff. Because we believe it is important to learn through real examples, we hope to ground our work in more case studies to be released over the next few months, as more features become available.

To get started, see the Fairness Indicators GitHub repo. For more information on how to think about fairness evaluation in the context of your use case, see this link.

We would love to partner with you to understand where Fairness Indicators is most useful, and where added functionality would be valuable. Please reach out at tfx@tensorflow.org to provide any feedback on your experience!

Acknowledgements
The core team behind this work includes Christina Greer, Manasi Joshi, Huanming Fang, Shivam Jindal, Karan Shukla, Osman Aka, Sanders Kleinfeld, Alicia Chang, Alex Hanna, and Dan Nanas. We would also like to thank James Wexler, Mahima Pushkarna, Meg Mitchell and Ben Hutchinson for their contributions to the project.