How to easily change your Apple Music playlists cover art

Make your playlists truly your own. Here’s how to easily change your Apple Music playlist cover art on both iPhone and Mac.

iPhone Apple Music Playlist Change Cover Art

When you create a playlist with Apple Music, the cover art of the albums for your first four selected songs pop in as your playlist cover by default. If you would prefer to have a different image, you can change it.

Here’s how to easily change your Apple Music playlist cover art.... Read the rest of this post here


"How to easily change your Apple Music playlists cover art" is an article by iDownloadBlog.com.
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Why you need a supercomputer to build a house

When the hell did building a house become so complicated? Don’t let the folks on HGTV fool you. The process of building a home nowadays is incredibly painful. Just applying for the necessary permits can be a soul-crushing undertaking that’ll have you running around the city, filling out useless forms, and waiting in motionless lines […]

When the hell did building a house become so complicated?

Don’t let the folks on HGTV fool you. The process of building a home nowadays is incredibly painful. Just applying for the necessary permits can be a soul-crushing undertaking that’ll have you running around the city, filling out useless forms, and waiting in motionless lines under fluorescent lights at City Hall wondering whether you should have just moved back in with your parents.

Consider this an ongoing discussion about Urban Tech, its intersection with regulation, issues of public service, and other complexities that people have full PHDs on. I’m just a bitter, born-and-bred New Yorker trying to figure out why I’ve been stuck in between subway stops for the last 15 minutes, so please reach out with your take on any of these thoughts: @Arman.Tabatabai@techcrunch.com.

And to actually get approval for those permits, your future home will have to satisfy a set of conditions that is a factorial of complex and conflicting federal, state and city building codes, separate sets of fire and energy requirements, and quasi-legal construction standards set by various independent agencies.

It wasn’t always this hard – remember when you’d hear people say “my grandparents built this house with their bare hands?” These proliferating rules have been among the main causes of the rapidly rising cost of housing in America and other developed nations. The good news is that a new generation of startups is identifying and simplifying these thickets of rules, and the future of housing may be determined as much by machine learning as woodworking.

When directions become deterrents

Photo by Bill Oxford via Getty Images

Cities once solely created the building codes that dictate the requirements for almost every aspect of a building’s design, and they structured those guidelines based on local terrain, climates and risks. Over time, townships, states, federally-recognized organizations and independent groups that sprouted from the insurance industry further created their own “model” building codes.

The complexity starts here. The federal codes and independent agency standards are optional for states, who have their own codes which are optional for cities, who have their own codes that are often inconsistent with the state’s and are optional for individual townships. Thus, local building codes are these ever-changing and constantly-swelling mutant books made up of whichever aspects of these different codes local governments choose to mix together. For instance, New York City’s building code is made up of five sections, 76 chapters and 35 appendices, alongside a separate set of 67 updates (The 2014 edition is available as a book for $155, and it makes a great gift for someone you never want to talk to again).

In short: what a shit show.

Because of the hyper-localized and overlapping nature of building codes, a home in one location can be subject to a completely different set of requirements than one elsewhere. So it’s really freaking difficult to even understand what you’re allowed to build, the conditions you need to satisfy, and how to best meet those conditions.

There are certain levels of complexity in housing codes that are hard to avoid. The structural integrity of a home is dependent on everything from walls to erosion and wind-flow. There are countless types of material and technology used in buildings, all of which are constantly evolving.

Thus, each thousand-page codebook from the various federal, state, city, township and independent agencies – all dictating interconnecting, location and structure-dependent needs – lead to an incredibly expansive decision tree that requires an endless set of simulations to fully understand all the options you have to reach compliance, and their respective cost-effectiveness and efficiency.

So homebuilders are often forced to turn to costly consultants or settle on designs that satisfy code but aren’t cost-efficient. And if construction issues cause you to fall short of the outcomes you expected, you could face hefty fines, delays or gigantic cost overruns from redesigns and rebuilds. All these costs flow through the lifecycle of a building, ultimately impacting affordability and access for homeowners and renters.

Startups are helping people crack the code

Photo by Caiaimage/Rafal Rodzoch via Getty Images

Strap on your hard hat – there may be hope for your dream home after all.

The friction, inefficiencies, and pure agony caused by our increasingly convoluted building codes have given rise to a growing set of companies that are helping people make sense of the home-building process by incorporating regulations directly into their software.

Using machine learning, their platforms run advanced scenario-analysis around interweaving building codes and inter-dependent structural variables, allowing users to create compliant designs and regulatory-informed decisions without having to ever encounter the regulations themselves.

For example, the prefab housing startup Cover is helping people figure out what kind of backyard homes they can design and build on their properties based on local zoning and permitting regulations.

Some startups are trying to provide similar services to developers of larger scale buildings as well. Just this past week, I covered the seed round for a startup called Cove.Tool, which analyzes local building energy codes – based on location and project-level characteristics specified by the developer – and spits out the most cost-effective and energy-efficient resource mix that can be built to hit local energy requirements.

And startups aren’t just simplifying the regulatory pains of the housing process through building codes. Envelope is helping developers make sense of our equally tortuous zoning codes, while Cover and companies like Camino are helping steer home and business-owners through arduous and analog permitting processes.

Look, I’m not saying codes are bad. In fact, I think building codes are good and necessary – no one wants to live in a home that might cave in on itself the next time it snows. But I still can’t help but ask myself why the hell does it take AI to figure out how to build a house? Why do we have building codes that take a supercomputer to figure out?

Ultimately, it would probably help to have more standardized building codes that we actually clean-up from time-to-time. More regional standardization would greatly reduce the number of conditional branches that exist. And if there was one set of accepted overarching codes that could still set precise requirements for all components of a building, there would still only be one path of regulations to follow, greatly reducing the knowledge and analysis necessary to efficiently build a home.

But housing’s inherent ties to geography make standardization unlikely. Each region has different land conditions, climates, priorities and political motivations that cause governments to want their own set of rules.

Instead, governments seem to be fine with sidestepping the issues caused by hyper-regional building codes and leaving it up to startups to help people wade through the ridiculousness that paves the home-building process, in the same way Concur aids employee with infuriating corporate expensing policies.

For now, we can count on startups that are unlocking value and making housing more accessible, simpler and cheaper just by making the rules easier to understand. And maybe one day my grandkids can tell their friends how their grandpa built his house with his own supercomputer.

And lastly, some reading while in transit:

Cover collects $16M to insure your gadgets, pets… anything

People procrastinate about buying insurance because it’s such a boring and complicated chore to compare policies. But Cover combines plans from 45 insurance companies into a single marketplace so it’s easy to find the best one for your car, home, rental, business, personal property, pets, jewelry and more. Now Cover is building powerful onboarding tricks […]

People procrastinate about buying insurance because it’s such a boring and complicated chore to compare policies. But Cover combines plans from 45 insurance companies into a single marketplace so it’s easy to find the best one for your car, home, rental, business, personal property, pets, jewelry and more. Now Cover is building powerful onboarding tricks like a driving school that earns you lower car insurance rates, and a way for Shopify merchants to sell warranties for their items.

The potential to use tech to run circles around the old insurance brokers has attracted a new $16 million Series B for Cover led by Tribe Capital’s Arjun Sethi, who led the Series A and sits on the startup’s board. The round was joined by Y Combinator, Social Capital, Exor and Samsung, and brings the company to a total of $27.1 million in funding.

“Insurance isn’t very different from being a white-collar bookie, where the house’s rake is too high and the dollars at stake are in the hundreds of billions in the U.S. alone,” says co-founder and CEO Karn Saroya. “This, all to the detriment of regular people, who view insurance as a tax. We’re here to change that perception.”

Saroya and his co-founders have deep ties. He went to high school with Anand Dhillon, is engaged to Natalie Gray and hired Ben Aneesh at the team’s previous startup, a high-end fashion marketplace called StyleKick that was eventually acqui-hired by Shopify. “We were tossing around ideas for what we wanted to do after StyleKick/Shopify, running hackathons on weekends. We built a couple different apps, but Cover — the MVP, where we just asked potential customers to take pictures of things they wanted to insure, surprised us” says Saroya. “Our customers sent us walkthroughs of their homes, pictures of their dogs and videos of themselves washing their cars. When you come across behavior that violates your expectations in consumers, that’s usually when you double-down.”

Cover co-founder and CEO Karn Saroya

So they built Cover, where you don’t have to cobble together an endless set of insurance websites or wait on hold. You download the app, pick your item, list how much you paid and where, provide some photos or video of its condition using its TensorFlow-equipped camera and Cover will check across its insurance partners and find you the best quote instantly. You can easily see what is and isn’t covered, learn how to make claims, and text with an agent if you have questions. For example, I was quickly quoted $5 per month to insure my new iPhone against damage but not loss or theft.

Cover earns between 10 to 35 percent per dollar of premium you pay. Its annualized premium already exceeds $8.5 million and is growing 30 percent per month. Thanks to its low-churn business model, easy cross-promotion of products, low training requirements for customers and no need to constantly update its existing subscriptions, Cover starts to look like a very efficient software-as-a-service business.

The big question remains whether Cover can consistently find the best rates for customers so they don’t second guess its quotes and search somewhere else. It will have to outcompete multi-insurance providers, like State Farm and Geico, as well as startups like MetroMile tackling specific insurance verticals with mobile apps. To really earn the big profits, Cover is building out its own in-house insurance plans. But that will put it under constant threat of insuring the wrong risks and ending up paying out too much.

“We built Cover because we saw an opportunity to build elegant products that could deliver on pricing and customer experience in a way that no incumbent insurance entity can,” Saroya concludes. By bringing the service to mobile and making it a seamless part of owning something, Cover could ensure you’re insured, even if insurance is the last thing you want to think about.