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:

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/
The venture potential of a startup that caters to individual students — instead of a slow-moving, small-pocketed institution — has a bullish aura that attracts investors.
Add in a pandemic that forced many to embrace remote learning overnight, and it makes sense that we have seen companies like Outschool and ClassDojo turn first profits while startups like Quizlet and ApplyBoard reached $1 billion valuations.
Last year brought a flurry of record-breaking venture capital to the sector. PitchBook data shows that edtech startups around the world raised $10.76 billion last year, compared to $4.7 billion in 2019. While reporting delays could change this total, VC dollars have more than doubled since the pandemic began. In the United States, edtech startups raised $1.78 billion in venture capital across 265 deals during 2020, compared to $1.32 billion the prior year.
In today’s survey, thirteen top edtech investors shared their thoughts on how growth of lifelong learning is reshaping the industry. Given the sudden extinction of snow days and yeast shortages brought on by student bakers in the early days of the pandemic, it’s easy to see how remote education extends beyond traditional school hours. As learners become more multi-layered and nuanced, so have the edtech companies that back them.
This was a recurring theme in today’s survey, signaling a shift in how investors approach hybrid learning. The evolution of post-pandemic education will be complex, if not aggressively competitive among the growing cohort of well-capitalized edtech companies. While we asked investors about their post-pandemic tastebuds back in July, much has changed since. Higher education didn’t combust like some expected today, and today, many predict that K-12 students will return to pre-COVID formats after vaccinations are widespread.
It puts startups in a difficult spot: if 2020 was about enabling video-based teaching, what might emerge from 2021? Integration between different edtech apps? New student collaboration tools? Are employer-led up-skilling and a renewed interest in self-improvement enlarging edtech’s TAM?
Here are the investors we spoke to, along with their areas of interest and expertise:
What will edtech look like when students finally go back to school in person? Now that remote has become familiar, what are other concepts that you could see becoming popular?
For k12, use of digital products and platforms will now be very “normal” – companies like Lexia and Dreambox and Nearpod. Maybe this drives home usage of some products traditionally used only in schools like Lexia. Students of all ages are now very facile with zoom, this can pave the way for more zoom based synchronous learning offerings including extracurricular learning like music, dance etc. schools are now fully wired – maybe we will see schools implement home based learning programs – it’s where students spend half their time.
What are the biggest hurdles ahead for early-stage edtech startups looking to scale? What opportunities are fading as the space matures?
Edtech cos need to stay away from the me too solutions. We have seen 20 creator led learning platforms across “preK to Gray” learning in addition to incumbents like Teachable and very few have an ability to build a moat in my view. Unless someone has a very fresh take, I think that ship has sailed. Hopefully as white spaces fill with competitors, new white spaces will emerge. Emerging tech – AI/NLP/ML/VR – will continue to push the envelope. We are still not driving enough people to competency whether in prek12, higher ed or workforce so the opportunity remains vast.
How has edtech’s boom impacted your dealmaking? Has the new interest from generalist investors made valuations too bubbly, or is the market growth helping everyone?
We met on zoom with over 800 founding teams in covid all over the world. We invested in 14 new companies and are just finishing rounds in 2 more. Valuation pressures are across tech sectors. Id argue that education still lags average tech. the question for edtech is whether there is potential for a $100B company in the sector – will TAMs support it.
What will edtech look like when students finally go back to school in person? Now that remote has become familiar, what are other concepts that you could see becoming popular?
As it relates to our thesis, I believe that the role of employers is changing. Pre-COVID, it was estimated that as much as 1/3 of the US workforce would need to change jobs by 2030. Employers cite skills gaps as a top 3 business concern to stay competitive. Our thesis is that employers will take on more responsibility for reskilling their current workforce, and that training will become job-embeded (rather than only trying to hire to address the challenge.) Degreed was the first wave of this… Learn In is an example of the next step in this evolution. As employers look to provide more skills training (rather than compliance training), we believe that more will come from external sources (CEOs say they are unprepared to meet the reskilling challenge with existing internal resources) and that much of this training will be provided online and during work hours (to address the time barrier that is an equity issue.) I also see an opportunity for modalities like VR to become more popular as we shift to more digital and remote solutions (e.g TRANSFR.) Stats from McKinsey research.
What are the biggest hurdles ahead for early-stage edtech startups looking to scale? What opportunities are fading as the space matures? In US pre-K and K-12, high customer fragmentation (16,000 school districts, 100K+ schools…pre-K even more fragmented with little public investment), long sales cycles, budget, pedagogy, and regulation. TAM. Relatively low consumer spend on education relative to other markets. Opportunities – increasing access to broadband, increase in device penetration. In FOW, increased recognition that reskilling and upskilling is a business imperative, company culture matters for competitiveness, increased focus on DEI.
What will edtech look like when students finally go back to school in person? Now that remote has become familiar, what are other concepts that you could see becoming popular?
I think activities that are fundamentally better in person will go back to [being] in person (e.g., sports, music and other enrichment activities). I think that new technology educators may have adopted during the pandemic that they have found to be helpful to their instruction will remain but all the “nice to haves” will likely fall to the wayside. We have a thesis at Cowboy that supplemental education (e.g., Juni Learning, Reconstruction or Outschool) will likely stay online, because parents will not have to worry about driving their kids to learning centers and these companies have the opportunity to make the learning fun.
What are the biggest hurdles ahead for early-stage edtech startups looking to scale? What opportunities are fading as the space matures?
For companies focused on K-12 students, it’s still really challenging to sell into schools and school districts because of the long sales cycle. This will likely become even harder, as local and state budgets tighten. In regard to what is fading, I think that tools that don’t solve a real need for educators, students and/or parents or don’t have demonstrated efficacy when it comes to student outcomes will start to fade. Consumers, especially after the pandemic, seem to be more aware of what technology has to offer and have lower tolerance for tools not having a demonstrable impact.For companies that are targeting adult learners, the biggest hurdle continues to be customer acquisition and building a brand that learners can actually trust. As the space starts to mature, consumers are getting more aware of the questions they should be asking (e.g., graduation and placement outcomes) and are less [fooled] by clever marketing.
What do you expect education to look like in five-plus years from now, when the pandemic is more of a memory?
I hope that in this pandemic we’ve realized how critical our educators are to our children’s success and we pay them more :) Incentivizing our best talent to get into and stay in teaching is a critical lever we can pull to improve education.
For K-12, I expect that there will be more comfort with technology in the classroom and that tech can be partnered with in-person instruction in a way that supercharges the educator with the data needed to personalize their instruction.
For higher ed, I expect that there will be an acceleration in online learning for adults as they continue to look to reskill or upskill. There will be more opportunities to do self-paced online learning that is effective and affordable.
What will edtech look like when students finally go back to school in person? Now that remote has become familiar, what are other concepts that you could see becoming popular?
In K-12, education will probably continue to look much like it did, because the majority of parents are clear that child care is the principal value for their kids being at school. That said, a minority of parents are certainly rethinking education after witnessing what their children were actually learning every day for a year. My opinion is that we will continue to see a disaggregation of this care function from academics. Here’s a piece I wrote about that, which has accelerated significantly this year.
What are the biggest hurdles ahead for early-stage edtech startups looking to scale? What opportunities are fading as the space matures?
For vocational schools with a “free until you get a job” model like Lambda or SV Academy, it’s all about job placement. Lambda has had a lot of success with their new fellowship model, which has allowed them to scale significantly. For a lot of early childhood and K-12 companies working online, it’s about new parent behaviors and whether you can develop a habit like Outschool has done. For senior learning like what GetSetUp does, finding the reimbursement models through healthcare is probably the key.
What do you expect education to look like in five-plus years from now, when the pandemic is more of a memory?
I think we are in a transition to more and more academics happening in the cloud. Right now, that’s all about live experiences and human in the loop. In five years, I think we will begin seeing a significant impact of AI replacing many human functions.
Source: https://techcrunch.com/2021/01/28/12-investors-say-lifelong-learning-is-taking-edtech-mainstream/
UCLA researchers have been awarded a $3.65 million grant to collect, contextualize, and digitally preserve a huge archive of materials relating to policing and mass incarceration. It should help historians and anthropologists, but more fundamentally it will thoroughly document a period that many would rather forget.
The “Archiving the Age of Mass incarceration” effort is being led by Kelly Lytle Hernandez, director of the university’s Bunche Center for African American Studies and creator of Million Dollar Hoods, another project documenting the human cost of incarceration in Los Angeles. The grant is provided by the Andrew W. Mellon Foundation.
“We may be at a turning point in American history — may be building something new,” Lytle Hernandez told me, citing a tumultuous but potentially transformative 2020. “If that’s the case we want to make sure we are preserving the record of what happened. What we want to do is retain the records, the memory, the experiences of people affected by mass incarceration, and where possible the records of the state, which would otherwise be destroyed.”
The core of this collection will be a cache of documents released to Lytle Hernandez by the LAPD as part of this 2019 settlement (shortly after she won a MacArthur fellowship) regarding public disclosures and communication. She described it as around 177 boxes of paper records from the 1980s to the early 2000s detailing the “war on drugs,” policing immigrants, and many other topics, with more to be provided later under an agreement with the department.
The idea would be to “counterbalance” these official documents, as she put it, with documentation and testimony from the other side of the equation.
“People who are disproportionately incarcerated or arrested — we often lose our records because we get evicted; because where we stored our records, we can’t make the payments and they’re seized; they’re seized when we’re arrested, etc.,” she explained. “If we need to undo generations of harm, we need to know, where did that harm happen? Who did it happen to? I see this archival project as part of that dismantlement effort.”
Over the next few years Lytle Hernandez will lead the effort to assemble the archive, which will involve such traditional work as scanning and indexing paper documents, but also visiting communities and collecting “carceral ephemera” such as receipts for bail bonds (which may be the only surviving record of a person’s brush with the justice system) and personal stories and media.
Getting records from police and state agencies is a difficult and sometimes legally or politically fraught process. It’s important to get as much information as possible, from as many sources as possible, as quickly as possible, she said. Other major turning points in the history of racial justice have been inadequately documented, for reasons both negligent and deliberate.
“What if the nation had sent out squads of oral historians and students to capture and preserve the record? Imagine what we could know about enslavement and its toll on all of us, what it meant to the making of this country, if we had talked to the people who had experienced it — what kind of archive that would have left us, to grapple with and to help us move away from its legacies,” said Lytle Hernandez. “But we’ve been able to forget the power and legacy of slavery because we didn’t do a good enough job. Same with native removal, internment, immigration.”
Now there is an opportunity — around the country, she was careful to point out, not just in LA — to do just that with the era of mass incarceration. Not only that but they can bring modern techniques to bear in ways that weren’t possible during, say, the Civil Rights movement.
Her experience with Million Dollar Hood has shown her that there is serious interest in turning the tables among communities that have historically been disenfranchised or targeted by racist and classist policies propped up by bogus data.
“When we have a meeting we have black and brown students crammed into the room and out into the hall to learn data analysis and data science,” she said. “Part of the project is opening up that door. When you bring the people into the room who are the most impacted, they see that data differently — they see different stories.”
The archive will be completely public, though the exact scope of what documents will be included and how they will be sorted, described, and so on is still being worked out. Regardless of the exact details, the archive should prove invaluable to students, researchers, and a curious public over the coming decades as the changes Lytle Hernandez hopes for begin to get underway.