In spring 2012, along with investigative journalist and former Computer Weekly executive editor Tony Collins , I submitted freedom of information (FOI) requests to the Department for Work and Pensions (DWP) for four key documents about its controversial IT-enabled welfare reform programme, Universal Credit. Little did either of us know then that, four years later, we would still be fighting for their release.
The documents – a risk register, an issues log, a milestone schedule and a project assessment review (PAR) report – could potentially reveal the truth about a high-profile government project that was already rumoured to be in trouble .
I submitted my request because there was obviously a gulf between the scale of what was being promised by the programme and the published completion date of October 2017. To add insult to injury, the DWP had opted to use agile development , even though it had no experience of the methodology and it had not been proven in government on this scale and scope.
I am not anti-agile by any means, but trying something new purely because it is perceived to be the only way to meet the department’s challenging timetable is not sensible.
Anyone familiar with government departments and FoI requests will not be surprised to hear that the DWP refused to release the documents. After complaining to the information commissioner, who agreed that everything but the risk register should be disclosed, our case proceeded to a tribunal hearing in January 2014. This unanimously decided that all four documents should be released.
The DWP was not happy and appealed on a legal point to the Upper Tribunal (UT), where it won. Despite the same UT judge suggesting that, given the age of the information by this time, the DWP should consider releasing the documents, the department insisted on the expense of yet another oral hearing. This took place in February this year and the result was exactly the same as in 2014 – that the DWP should hand over the reports.
After nearly four years, we now have to wait another 28 days to see if the DWP finally discloses the information or tries to appeal once again. The legal costs for the taxpayer associated with this marathon must comfortably exceed £100,000.
With containers gaining increasing popularity in enterprise environments across a variety of industries to automate the deployment of applications, Joyent and others in the container ecosystem got together to give a state-of-the-state event at the Container Summit conference Feb. 10 in New York City. Although the cloud native world is adopting container technologies, such as Docker, only 8 percent of enterprises are using them in production, said Dave Bartoletti, a principal analyst at Forrester Research. Yet curiosity about containers is soaring. Bartoletti said questions from clients about containers and when and how to deploy them have increased by a factor of 10 in the last two years. Indeed, many of the speakers at the Container Summit said they were introduced to container technology in a previous job and moved it to their current role. Others simply adopted it as the proper thing to do. This eWEEK slide show looks at some of the scenes from the Container Summit and what industry experts had to say about the technology.
Black Duck , which provides automated solutions for securing and managing open-source software, has announced its annual Open Source Rookies of the Year awards, recognizing the top new open-source projects initiated in 2015. Patrick Carey, Black Duck's director of product management, who headed the selection process, said the chosen projects show how diverse and ambitious open-source software development has become. "This year's Rookies are impressive examples of how far open source has come, with start-ups like Mattermost and Glucosio as well as big players like Google, Facebook and Red Hat leveraging the open-source community to help drive innovation in everything from DevOps and Docker container solutions to diabetes monitoring and real-time communication," he said. The 2015 Rookies class reflects three hot technologies shaping the future of open-source software: Docker containers, open collaboration and artificial intelligence. In 2014, a number of Docker ecosystem players emerged, and the trend continued into 2015 with several, including projects sponsored by Red Hat and Capital One. This eWEEK slide show looks at the winners and honorable mentions of the 2015 Black Duck Rookie of the Year awards.
As a fan of Cossack dancing, Eastern Bloc architecture, vodka and pervasive government oppression, Sneak loves Russia.
And while he accepts that Siberia is a vast and mostly empty land mass, capable of killing the unwary in numerous ways, he would not liken it to Mordor, the dark, ash-covered, orc-infested land in the south-east of Tolkien's Middle Earth.
But, according to multiple reports, the all-seeing, all-knowing Sauron Google believes that Russia is in fact Mordor. Or more accurately a bug in the Google Translate tool translated the Ukrainian word for 'Russian Federation' into 'Mordor'.
Not content with effectively calling Russia a nation of twisted, down-trodden creatures ruled by a brutal dictator, Google Translate went one step further by translating 'Russians' into 'okkupanty' meaning ‘occupiers' in Sneak's second language, that being English. C++ is his mother tongue.
Then to pour a granary of salt into the virtual wound, Google translated the surname of Russian foreign minister Sergey Lavrov into the Russian for 'sad little horse', according to The Telegraph. Sneak thinks that's rather cute in a slightly Eeyore way. Yes he knows Eeyore is a fictional donkey. Please don't write in.
Now, that noise you're hearing is Sneak's irony alarm going off at full pelt, given that Ukraine is not exactly having the best time with Russia and pro-Russian rebels at the moment, particularly as in 2014 Russia annexed the Crimea region from Ukraine, simply because it could.
Google has apologised for the error and blamed the automated aspect of Translate, but Sneak is not convinced that it was a bug and, to indulge the conspiracy theorist in him, believes that a disgruntled pro-Ukraine programmer decided to tweak Google Translate to offer this slight at Russian users.
Back in his early years as an IT chap at Northern Rock, Sneak ended up dating a lovely Russian systems analyst called Natasha. She had a mononym.
Next thing he knew she disappeared one evening after a heady mix of vodka and Kerplunk! and disappeared with Sneak's server room key card. Then the banking crisis happened, Northern Rock went under and Sneak took indefinite sick leave.
The moral of the story is that annoying the Russians might not be wise, otherwise the road to Google's Mountain View HQ could end up being blocked by Soviet-era tanks with president Putin straddling a turret, topless and declaring "You shall not pass" to befuddled Google engineers.
Or perhaps they will take it in good humour. After all as the video below explains: Russians love to boogie.
07 Jan 2016
After years of hype, virtual reality is really entering the gaming market. By the end of the month, the Oculus Rift VR headset will be available to consumers for $600 , though those with less than top-of-the-line PCs may need to commit to getting the $1,500 package that includes an Oculus Ready PC. About the same time, Microsoft HoloLens is set to ship to developers for $3,000. The HTC Vive VR headset ($800), which also requires an up-to-date gaming PC, should be available to consumers in early April.
Back in November, Samsung released its Gear VR headset for $100. Google is expected to unveil an updated version of its $15 Cardboard VR viewer this year. Sony, meanwhile, is planning to ship its PlayStation VR headset in October for $400 (a separate camera and a PlayStation unit are also necessary).
With the hardware, there will actually be some compelling content. At least 30 VR-ready games will be available for the Oculus Rift when it ships, thanks to efforts to spur developer interest going back to GDC 2015 and the year before, when Facebook acquired Oculus and investment in VR technology took off. Among the more impressive titles is Eve: Valkyrie , a multiplayer space combat simulation. It promises both visuals that impress and character persistence to keep players engaged. VR and MMOs should work well together.
This year at the Game Developers Conference 2016 -- run by InformationWeek's parent company UBM -- there was a two-day summit devoted to VR, the Virtual Reality Developers Conference .
Yet for all the enthusiasm about VR among platform companies, game companies, and hardware makers, mobile and otherwise, VR still has a lot to prove. Recall the hype surrounding 3D television? It took off at CES, starting in 2011, and continued more or less until earlier this year when Samsung and LG showed signs of backing away from the technology. 3D just doesn't add enough to TV viewing to make it worth the bother.
VR adds more and it may add up. Gartner expects sales of head-mounted displays will surge, up from 140,000 in 2015 to 1.43 million this year. That's a start. But with smartphones moving at rate of more than a billion per year, VR has a long way to go before it becomes a mass-market medium. There's reason to doubt it will ever be more than specialty experience.
[Read 18 Most Anticipated Video Games of 2016 .]
VR is a path to funding and a revenue generator for cloud companies and makers of graphics software. It can offer an exceptional entertainment experience for a price, provided you don't mind wearing a ridiculous-looking headset that limits your ability to function in the real world. It has one advantage: It's expensive enough to produce that VR companies don't have to worry about indie developers saturating the market, as they've done with mobile games.
Just as 3D movie technology hasn't eliminated traditional cinema, VR won't change the nature or social function of electronic games, mobile or otherwise. It will expand gaming and entertainment, providing a premium experience and enabling new forms of creative expression. But it won't necessarily lead to better storytelling or better game design. A soulless, derivative shooting game won't become a work of sublime inspiration simply because it can be experienced through goggles.
At GDC 2016, developers lined up to experience VR firsthand. The pictures that follow should give you a sense of both the excitement surrounding the technology and its absurdity. Take a look and let us know what you think in the comments section below.
For those with South by FOMO or who want to relive past week glories, we present to you images of this year’s SXSW festivities in Austin, Texas. Flip through the fun. You might even find yourself or a friend in there somewhere.
There is no question that machine learning is at the top of the hype curve. And, of course, the backlash is already in full force: I’ve heard that old joke “Machine learning is like teenage sex; everyone is talking about it, no one is actually doing it” about 20 times in the past week alone.
But from where I sit, running a company that enables a huge number of real-world machine-learning projects, it’s clear that machine learning is already forcing massive changes in the way companies operate.
It’s not just futuristic-looking products like Siri and Amazon Echo. And it’s not just being done by companies that we normally think of as having huge R&D budgets like Google and Microsoft. In reality, I would bet that nearly every Fortune 500 company is already running more efficiently — and making more money — because of machine learning.
So where is it happening? Here are a few behind-the-scenes applications that make life better every day.
The average piece of user-generated content (UGC) is awful. It’s actually way worse than you think. It can be rife with misspellings, vulgarity or flat-out wrong information. But by identifying the best and worst UGC, machine-learning models can filter out the bad and bubble up the good without needing a real person to tag each piece of content.
A similar thing happened a while back with spam emails. Remember how bad spam used to be? Machine learning helped identify spam and, basically, eradicate it. These days, it’s far more uncommon to see spam in your inbox each morning. Expect that to happen with UGC in the near future.
Pinterest uses machine learning to show you more interesting content. Yelp uses machine learning to sort through user-uploaded photos. NextDoor uses machine learning to sort through content on their message boards. Disqus uses machine learning to weed out spammy comments.
It’s no surprise that as a search company, Google was always at the forefront of hiring machine-learning researchers. In fact, Google recently put an artificial intelligence expert in charge of search. But the ability to index a huge database and pull up results that match a keyword has existed since the 1970s. What makes Google special is that it knows which matching result is the most relevant; the way that it knows is through machine learning.
But it’s not just Google that needs smart search results. Home Depot needs to show which bathtubs in its huge inventory will fit in someone’s weird-shaped bathroom. Apple needs to show relevant apps in its app store. Intuit needs to surface a good help page when a user types in a certain tax form.
Successful e-commerce startups from Lyst to Trunk Archive employ machine learning to show high-quality content to their users. Other startups, like Rich Relevance and Edgecase , employ machine-learning strategies to give their commerce customers the benefits of machine learning when their users are browsing for products.
You may have noticed “contact us” forms getting leaner in recent years. That’s another place where machine learning has helped streamline business processes. Instead of having users self-select an issue and fill out endless form fields, machine learning can look at the substance of a request and route it to the right place.
That seems like a small thing, but ticket tagging and routing can be a massive expense for big businesses. Having a sales inquiry end up with the sales team or a complaint end up instantly in the customer service department’s queue saves companies significant time and money, all while making sure issues get prioritized and solved as fast as possible.
Machine learning also excels at sentiment analysis. And while public opinion can sometimes seem squishy to non-marketing folks, it actually drives a lot of big decisions.
For example, say a movie studio puts out a trailer for a summer blockbuster. They can monitor social chatter to see what’s resonating with their target audience, then tweak their ads immediately to surface what people are actually responding to. That puts people in theaters.
Another example: A game studio recently put out a new title in a popular video game line without a game mode that fans were expecting. When gamers took to social media to complain, the studio was able to monitor and understand the conversation. The company ended up changing their release schedule in order to add the feature, turning detractors into promoters.
How did they pull faint signals out of millions of tweets? They used machine learning. And in the past few years, this kind of social media listening through machine learning has become standard operating procedure.
Dealing with machine-learning algorithms is tricky. Normal algorithms are predictable, and we can look under the hood and see how they work. In some ways, machine-learning algorithms are more like people. As users, we want answers to questions like “why did The New York Times show me that weird ad” or “why did Amazon recommend that funny book?”
In fact, The New York Times and Amazon don’t really understand the specific results themselves any more than our brains know why we chose Thai food for dinner or got lost down a particular Wikipedia rabbit hole.
If you were getting into the machine-learning field a decade ago, it was hard to find work outside of places like Google and Yahoo. Now, machine learning is everywhere. Data is more prevalent than ever, and it’s easier to access. New products like Microsoft Azure ML and IBM Watson drive down both the setup cost and ongoing cost of state-of-the-art machine-learning algorithms.
At the same time, VCs have started funds — from WorkDay’s Machine Learning fund to Bloomberg Beta to the Data Collective — that are completely focused on funding companies across nearly every industry that use machine learning to build a sizeable advantage.
Most of the conversation about machine learning in popular culture revolves around AI personal assistants and self-driving cars (both applications are very cool!), but nearly every website you interact with is using machine learning behind the scenes. Big companies are investing in machine learning not because it’s a fad or because it makes them seem cutting edge. They invest because they’ve seen positive ROI. And that’s why innovation will continue.
A week ago yesterday, we told you that longtime Sequoia partner Michael Goguen had been slapped with a stomach-turning complaint. At its crux, it accused him of breaching an agreement he’d made to pay $40 million to a woman he’d known for years. Apparently, after paying her $10 million, Goguen concluded that he was within his rights to stop writing her checks. The woman then hired a lawyer.
Whether the case ever goes to trial is now beside the point for Goguen, who has enjoyed a lucrative career as a venture capitalist and who, fairly or unfairly, will now be publicly associated with that complaint and the person who filed it, despite his strongly worded counter-complaint .
Fairly or unfairly, it also does real damage to Sequoia Capital.
Entrepreneurs aren’t the immediate issue. It would take a lot more than this bizarre situation for most founders to be deterred from accepting a check from Sequoia, whose imprimatur can make everything easier, from assembling a team, to attracting press, to, later, luring the right investment bankers.
That Goguen is no longer a partner of Sequoia certainly minimizes the damage. (A spokesman didn’t elaborate when explaining to us last week why Sequoia decided Goguen’s departure was the “appropriate course of action.” But we suspect his original deal with his accuser was made without the firm’s knowledge, which would be a major no-no. That kind of financial agreement would be material information to a partnership.)
A much bigger problem for Sequoia will be recruiting female investing partners — something that longtime Sequoia investor Michael Moritz has said interests the firm.
You may recall his uncomfortable interview back in December with Bloomberg’s Emily Chang, when he told her that Sequoia “looks very hard [for female recruits] . .. We just hired a young woman from Stanford who is every bit as good as her peers and if there are more like her, we’ll hire them.” Moritz continued, “What we’re not prepared to do is to lower our standards.”
That “standards” comment immediately came back to bite Sequoia in the behind, and in light of what’s happening with Goguen, Moritz surely regrets it more than ever.
But no matter his intent, the firm will likely have even fewer choices now. It was already hard to imagine many top female operators who’d leap at the chance to work at an almost exclusively male venture firm. A situation like Goguen’s can only hurt its odds of drawing in smart women.
I don’t know anything about Sequoia’s internal dynamics. But partnerships are very small, intimate entities, in which people spend a lot of time socializing amongst themselves. That one of Sequoia’s partners had what now seems like a highly peculiar relationship with women would certainly raise a red flag for me, particularly following Moritz’s comments.
Maybe Sequoia feels like it did enough by distancing itself from Goguen. But for its own sake, the firm would be smart to do more. A detailed explanation of what they knew about Goguen’s behavior would help, as would Sequoia’s history of working with female entrepreneurs and female associates. It would also be nice to know whether and how Sequoia plans to help improve the gender issue more broadly in Silicon Valley.
As an eminent venture capital firm, it has a responsibility to do something.
Better sooner than later, too.
There is a growing consensus that autonomous vehicles (AVs) will soon be a reality. The debate today centers not on whether, but how soon, AVs will be commonplace on our roads. But for all the buzz surrounding AVs, many details about what a driverless future will look like remain unclear.
Which business models will work best for the commercialization of AVs? Which AV usage models will be most appealing for consumers? Which companies are best positioned to win in this new market?
These are big questions, and no certain answers can be given at this stage. Nonetheless, it is valuable to reflect, in a concrete way, on how this transformative technology might develop. This article will present some conjectures.
At a high level, two possible paradigms seem most likely for how society will use AVs. The first is private AV ownership. Under this model, individuals or families would continue to own their own vehicles and use them to get around. As the cars would be self-driving, exciting new possibilities exist for their use.
Individuals could be more productive while in transit. Children, the handicapped, the elderly and others not previously able to drive themselves could commute alone. People could earn supplemental income by sending their cars, when otherwise not in use, to transport other people or goods (a future version of on-demand services like Uber or Instacart).
This option would, in a way, be the closest thing to a continuation of the current status quo. Little would have to change about carmakers’ core business models: individual consumers would still make purchasing decisions and would own and operate their own vehicles.
The second paradigm for AV use represents a more radical reconceptualization of how people get around in society. Under this model, a shared fleet of autonomous vehicles would exist that individuals could summon on demand to get from Point A to Point B. After dropping off one passenger, the vehicle could then pick up and transport the next passenger. Individuals would have no need to own their own cars; rather, they would receive mobility “as a service.”
There are many details about a “mobility as a service” model that are intriguing to consider. The most straightforward version of this model is one in which individuals summon AVs on a one-off basis when they need to get somewhere, paying per ride or per mile — effectively, a driverless version of how Uber or Lyft work today.
It is also possible, however, to imagine the development of more sophisticated subscription models. Under a subscription model, individuals would pay a flat fee on a monthly or annual basis for unlimited access to a given fleet of vehicles, to be used whenever they need a ride — loosely analogous to a SaaS model.
One interesting question is the amount of segmentation that would develop among subscription offerings. It seems likely that, as with most other consumer products, a wide range of AV subscription types would become available that offer different benefits and features depending on price. These differently priced subscription offerings could vary in terms of the types of vehicles in the fleet, the average required wait time for a ride, the electronics and other features available inside the vehicles and so forth.
The issue of segmentation closely ties to the equally important question of which player or players would own and operate these AV fleets. One possibility is that auto manufacturers — at least those that choose to enter the AV market — could offer subscriptions to fleets consisting entirely of their vehicles. Thus, as an example, one could choose to subscribe to Ford’s AV fleet in a given city for a certain rate, or alternatively to pay more to subscribe to Mercedes’ fleet.
Alternatively, these shared AV fleets might be operated not by the carmakers themselves but rather by fleet providers that aggregate various makes of vehicles. To create a profitable role for themselves in the market, these providers would have to add value to the experience in some way beyond vehicle manufacture (e.g. sophisticated mapping or passenger-matching algorithms). One could speculate that Uber, which recently has invested heavily in autonomous technology, envisions itself playing a role along these lines.
One last issue worth contemplating regarding future AV use is the optimal size and capacity of vehicles. The majority of drives in the U. S. today are solo trips, meaning that vehicle space is significantly underutilized and fuel usage is needlessly high. It is statistically rare that all five seats in a standard sedan (much less all eight seats in an SUV) are in use.
Given this, it is plausible to imagine single-occupancy pods making up a significant portion of future AV fleets — thus increasing fuel efficiency, economizing on materials costs and taking up less space on roads. Perhaps vehicles with a wide range of different capacities (from single-occupancy pods all the way to small buses that can fit 20 or 30 people) will all exist on the road, in proportion to their demand, and customers can indicate their desired vehicle size when summoning a car.
In speculating about these possible AV business and usage models, it is important to keep in mind that this market will not necessarily be “winner take all.” It is altogether possible that more than one of these models — and others that have not yet even been imagined — will all coexist profitably in the market.
One need look no further than the current transportation market for an instructive analogy. Today, people get around in their daily lives in many different ways. Some people own their own cars. Some people rent cars when they need them (either through traditional car rental companies or newer models like Zipcar). Some people get everywhere through ride-sharing services like Uber or Lyft. Some people use public transportation or simply walk. People commonly switch from one of these solutions to another over the course of their lives depending on life’s changing circumstances.
The same will likely be true in the driverless future of tomorrow. For instance, shared fleet models may become prevalent, rendering the concept of private car ownership obsolete for many. At the same time, those who prefer may continue to own and operate their own AVs. Personal transportation is and will continue to be a massive market. There is room for many different models and companies to thrive, and it is unlikely that any one approach will win outright.
On a similar but broader note, many different types of companies will succeed in and add value to the autonomous vehicle space in different ways. It is highly unlikely that any one company will own the entire end-to-end AV experience (though if any company were to try, a plausible candidate would be Apple and its mysterious Project Titan). Instead, the AV experience is likely to be modularized across many different players.
For instance, profitable businesses will be built around producing: LIDAR sensors and other physical components for the vehicles; cybersecurity software to keep connected cars safe; high-performance computing chips to power the cars’ decision-making processes; consumer electronics for the cars’ interiors; mapping and geolocation software to enable the car to navigate; and much more. In this sense, AVs should be thought of not as a single new product but rather as an entirely new ecosystem in the economy.
The possibilities laid out above are, of course, speculative. As AVs continue to develop in the coming years, there will be many technology, product and business model advances that surprise us all. One way or another, autonomous vehicles’ impact on the way we live will be nothing short of transformative. It will be an exciting ride.
Apple might be currently talking about its unbreakable encryption and how it's a good thing for privacy, but the FBI ruing it. The privacy arguement certainly stannds up to scrutiny, but strong encryption can also be used as a weapon, as demonstrated by countless examples of ransomware. There are numerous breeds of ransomware out there , but one of the most prolific is TeslaCrypt.
It's just a year since the first version of TeslaCrypt appeared on the scene, and it's gone through various updates and iterations over the ensuing months. Now it's hit version 4 and as well as continuing to threaten victims with sharing their files online , it also boasts what is being referred to as 'unbreakable encryption'.
Heimdal Security warns that not only is the ransomware more powerful than ever, it has also been patched with a number of 'bug fixes'. This means that it is now better equipped to deal with very large files, while the use of RSA 4096 means that recovery of data is completely impossible. Specialists at Heimdal Security say that the previously-reliable TeslaDecoder tool is now worthless.
The latest version of the ransomware leaks even more information to remote server than previous releases. Heimdal Security says:
The speed with which TeslaCrypt is being developed is worrying, and it seems all but impossible for anti-malware tools to keep pace. In the event of infection, the only real recourse is to fall back on a backup, so the advice would be to make sure that one exists and is kept up to date. This of course does nothing to mitigate against the damage following the leaking of private data, whether it belongs to an individual or a company.
Photo credit: ronstik / Shutterstock
Microsoft has been keen to consigne Internet Explorer to the history books, but for a long time there has been a glaring issue with its successor, Microsoft Edge: a lack of extensions. With the release of Windows 10 Redstone build 14291 this finally changed.
While Microsoft Edge may now have extensions, it's still very early days and it's likely you'll find that most of your favorites are yet to make an appearance. But Microsoft has a plan. To make developers' lives as easy as possible, the company is working on a tool that will make it possible to port Chrome extensions to Edge.
As the Windows Store has failed to attract developers in droves, Microsoft will almost certainly be concerned that Edge's browser repository will be similarly ignored. It makes perfect sense to provide a way to port existing extensions from Chrome to Microsoft Edge, and in many ways it is an extension of the idea of making it easier to port apps from other platforms to Windows.
The news came from Microsoft Edge engineer Jabob Rossi who said on Twitter:
If you were hoping for a mountain of extensions to choose from, it seems that you might have a bit of a wait on your hands. Rossi says that -- to start with, at least -- extensions that make it to the Store will be hand-picked:
With a Chrome porting tool already in development, it would be strange if Microsoft didn’t also produce a tool to help Firefox plugin developers to bring their wares to Edge -- but there's no word on this at the moment.
Photo credit: T. Dallas / Shutterstock
SAN FRANCISCO (AP) — Microsoft says it was "unequivocally wrong" for hosting a party with scantily dressed female dancers during a video game developers' conference.
The party sparked a firestorm of criticism this week, in an industry that's been struggling to overcome longstanding complaints that it has objectified women and made them feel unwelcome as players and game-builders. In response, the head of Microsoft's Xbox division issued a statement saying the after-hours entertainment "represented Xbox and Microsoft in a way that was absolutely not consistent or aligned to our values. "
An Xbox spokeswoman declined to answer questions about the dancers, who wore abbreviated school-girl outfits as they reportedly greeted party-goers and danced on platforms. The party was held Thursday night during the annual Game Developers Conference in San Francisco.
Several people who attended the after-hours party complained on social media that they were offended and disappointed at seeing the go-go dancers. Some also noted the irony that, just hours earlier, Microsoft had sponsored a "Women in Gaming" luncheon to promote diversity in the industry.
In a statement, Xbox chief Phil Spencer acknowledged the event "disappointed many people" and pledged to "do better in the future. "
Xbox also released an email that Spencer sent to employees, which said the criticism was deserved. "I am personally committed to ensuring that diversity and inclusion is central to our everyday business," he added.
In an interview on "The Today Show" on Friday, Twitter CEO, Jack Dorsey, talked about Twitter's 10th anniversary, as well as confirm a few details on Twitter's future plans.
In conversation with show host, Matt Lauer, Dorsey confirmed that Twitter will be sticking to its 140-character limit for tweets, which blanks out previous suggestions by Dorsey that tweet limits may be raised to 10,000 .
This confirmation may come as a sigh of relief for long-time Twitter users, who feared that increasing the character limit to such a high value would have moved Twitter from one of its core features; being a micro-blogging site. Which is a fair assumption, as 10,000 characters is what you'd expect in a long-form blog post.
Whilst talking about the current limit remaining in place, Dorsey stated:
Can Twitter trust Dorsey, though? Days after announcing that Twitter isn't changing how timelines are ordered , they began pushing out an algorithmic change to timeline ordering .
Only time will tell.
The conversation soon turned to Twitter's behaviour policy, particularly harassment. On this, Dorsey explained that Twitter users can control harassment, through the use of blocking and not following people:
Dorsey clearly believes in letting users' themselves control what they can, and cannot see on the service.
Source: Today via Engadget