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New numbers from Canalys show a slowing in the major smartphone decline we saw for 2020. The past year was, of course, a major blow to an industry already suffering a slide. Hope that the arrival of 5G would right the ship were dashed by Covid-19.
Things are looking up, fueled in large part by a killer quarter for Apple. The company posted its earnings last night, putting much of its success at the feet of the iPhone 12. In spite (or perhaps because) of pandemic-fueled delays, the handset arrived in a perfect storm – the beginnings of a “supercycle” that see customers upgrading devices in a kind of critical mass.
Numbers are still down for the fourth quarter of 2020 – but they’re down by only 2% per the firm. That’s due in no small part to what amounted to the iPhone’s best quarter, as the company introduced four 5G-sporting handsets. Canalys shows a 4% increase for Apple, as the device arrived to a wider 5G rollout just in time for the holiday season.
The company snagged the global number one spot, with Samsung taking number two in spite of a 12% decline. Chinese manufacturers Xiaomi, Oppo and Vivo rounded out the top five, all seeing double digit increases, y-o-y.
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The category is expected to see a rebound this year, after suffering declines due first to supply chain concerns and then larger economic issues, stemming from the pandemic.
“The introduction of COVID-19 vaccines is also boosting business confidence for 2021, allowing them to plan and invest,” analyst Ben Stanton says of the figures. “Going forwards, there will be obvious economic ripple effects as government stimulus fades, and there are ongoing concerns around new virus strains. Overall though, sentiment in the industry is positive, and 2021 will see the smartphone market rebound after a 7% decline in 2020.”
Another report from Canalys notes more positive news for the PC market, showing a 35% y-o-y increase, courtesy of tablet and Chromebook sales.
General Motors has announced plans to be carbon neutral by 2040 — removing emissions from all of its products and global operations or offsetting those emissions through carbon credits or carbon capture within the next two decades.
The company also committed to have a fully electric fleet of vehicles by 2035.
It’s a big step for a company whose products are responsible for a large percentage of the greenhouse gas emissions that contribute to global climate change and comes on the heels of a pledge to launch a massive fleet of new electric vehicles and a $27 billion commitment to electrification late last year.
The auto giant said that it would work with the Environmental Defense Fun on its vision for an all-electric future and will work toward eliminating tailpipe emissions from light-duty vehicles by 2035.
GM’s also getting into the charging business too. The company said it would work with “governments, partners, and suppliers around the world too build out the necessary charging infrastructure and encourage the use of renewable energy n electric vehicle charging.”
To power the company’s operations, GM said it will use only renewable energy power at its U.S. facilities by 2030 and by 2035 all of its operations worldwide will use renewable power.
These commitments are also going to extend to its supply chain over time as the company works with its suppliers to reduce their emissions, increase transparency and source sustainable materials.
“While electric vehicles do not produce tailpipe emissions, it is critical that the impact associated with production and charging is incorporated in our plans. By working with utility companies to provide access to more renewable energy sources, GM hopes to address the entire production cycle of future EVs, with benefits that will extend far beyond our own vehicles and operations,” the company’s chief executive Mary Barra said in a statement.
This commitment is going to require a massive transformation that encompasses more than GM alone, Barra wrote, because “making the transition to an EV is simply not possible right now – either because the appropriate vehicles do not exist or because access to charging is limited where [people] live and work.”
Storetasker is an online marketplace focused on connecting Shopify merchants with developers and other experts who can help grow their business.
The product is now owned by the startup previously known as Lorem. Co-founder and COO Charlie Fogarty explained that while Lorem originally had a broader mission of connecting small businesses and developers, “We realized that Shopify and e-commerce was by far our best customer segment … so we basically acquired our main competitor, Storetasker, and merged the two business” under the Storetasker name.
The acquisition (which included the Storetasker product and expert network, but not the team) actually took place last year, and Fogarty said, “We’ve spent the last 10 months basically rebuilding the product from the ground up. We’ve taken years of learning and combined it into a rebrand, a new product and a new end-to-end customer experience.”
The core proposition is still the same, however. A Shopify merchant should be able to visit Storetasker, describe their project in simple terms and then within a few hours, Storetasker will match them up with one of the experts in the network, who they can work with directly.
Storetasker has already been used by more than 30,000 brands on Shopify, including Boll & Branch, Chubbies, Aisle, Alpha Industries, Truff Hot Sauce and Branch Furniture. Fogarty said the average project size is just $300 and usually involves adding custom designs and unique features to a Shopify store.
Image Credits: Storetasker
You could use a general marketplace like Upwork or Fiverr to find a freelance developer, but where Storetasker has conducted more than 5,000 interviews to vet its talent and picks the right expert for each customer, Fogarty said that on other platforms, “You have to sift through unvetted talent … The hiring burden is placed on the brand.”
Plus, he noted that brands can use Storetasker for more than development help — they also use it to find experts on conversion and “all the different aspects of e-commerce.”
In addition to the new product, Storetasker is also announcing that it raised $3.2 million in Series A funding last year from Flybridge, Founder Collective, and FJ Labs.
Looking ahead, Fogarty said he sees plenty of room to grow while remaining focused on the Shopify ecosystem. After all, there are more than 1 million stores on the platform, with $200 billion in total sales to date.
Source: https://techcrunch.com/2021/01/28/storetasker-relaunch/
A new type of neural network that’s capable of adapting its underlying behavior after the initial training phase could be the key to big improvements in situations where conditions can change quickly – like autonomous driving, controlling robots, or diagnosing medical conditions. These so-called ‘liquid’ neural networks were devised by MIT Computer Science and Artificial Intelligence Lab’s Ramin Hasani and his team at CSAIL, and they have the potential to greatly expand the flexibility of AI technology after the training phase, when they’re engaged in the actual practical inference work done in the field.
Typically, after the training phase, during which neural network algorithms are provided with a large volume of relevant target data to hone their inference capabilities, and rewarded for correct responses in order to optimize performance, they’re essentially fixed. But Hasani’s team developed a means by which his ‘liquid’ neural net can adapt the parameters for ‘success’ over time in response to new information, which means that if a neural net tasked with perception on a self-driving car goes from clear skies into heavy snow, for instance, it’s better able to deal with the shift in circumstances and maintain a high level of performance.
The main difference in the method introduced by Hasani and his collaborators is that it focuses on time-series adaptability, meaning that rather than being built on training data that is essentially made up of a number of snapshots, or static moments fixed in time, the liquid networks inherently considers time series data – or sequences of images rather than isolated slices.
Because of the way the system is designed, it’s actually also more open to observation and study by researchers, when compared to traditional neural networks. This kind of AI is typically referred to as a ‘black box,’ because while those developing the algorithms know the inputs and the the criteria for determining and encouraging successful behavior, they can’t typically determine what exactly is going on within the neural networks that leads to success. This ‘liquid’ model offers more transparency there, and it’s less costly when it comes to computing because it relies on fewer, but more sophisticated computing nodes.
Meanwhile, performance results indicate that it’s better than other alternatives for accuracy in predicting the future values of known data sets. Th next step for Hasani and his team are to determine how best to make the system even better, and ready it for use in actual practical applications.
Indian startup Shopalyst has officially launched a new platform that it calls the Discovery Commerce Cloud, which it says can help retailers take full advantage of digital advertising.
Co-founder and CEO Girish Ramachandra told me that Shopalyst was created to allow for “one seamless journey for the shopper” across advertising and e-commerce — something he said current systems are not currently designed to support.
The startup’s first product was a “universal buy button,” and Ramanchandra said that has “naturally progressed” into a broader set of tools for cross-platform advertising, which Shopalyst has been beta testing for the past year.
The Discovery Commerce Cloud consists of five modules, which Ramanchandra said work best together but can also be purchased separately. That includes:
- a market intelligence product with information about what consumers are searching for and what’s popular on media and e-commerce platforms
- an audience intelligence product to target ads based on audience interest, behavior and purchase intent
- a Universal Ads Manager to deliver ads across Google Ads, DV360, Facebook, Instagram, Amazon Ads, Twitter and TikTok
- a landing page builder that can support instant checkout on a brand’s own direct-to-consumer site, comparison shopping across e-commerce marketplaces, instant delivery or a physical store locator
- real-time metrics that measure the full customer funnel
Image Credits: Shopalyst
Ramachandra also noted that the ads created in the Universal Ads Builder optimized to each platform, with dynamically generated creative based on audience data. And by using the landing page builder, brands are also able to gather new data about the audience’s “shopping actions.”
“In the past, [brands] didn’t have shopping actions, because retailers don’t share that data back with them,” he said. “That is all changed. Now they’re able to acquire first-party data [from Shoplalyst], which will help them use the right advertising in future campaigns.”
Shopalyst customers include Unilever, Nestle, Diageo, Nivea, L’Oreal and Estee Lauder. And while the startup was initially focused on its home market of India, the platform is now available across 30 countries.
Shopalyst also says that in beta testing, campaigns run through the Discovery Commerce Cloud have seen up to a 3X improvement in targeting relevance, a 5X increase in audience attention and an 8X increase in ad-activated shopping trips.
Source: https://techcrunch.com/2021/01/28/shopalyst-discovery-commerce-cloud/
