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This CEO Doesn’t Look at Resumes When Hiring

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Working in software engineering, Aline Lerner saw firms overlook promising candidates who didn’t have fancy schools or top companies on their resumes. Her company, Interviewing.io, helps them get a foot in the door.

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This story originally appeared on PC Mag

Ivy League degrees and stints at top firms don’t necessarily impress Aline Lerner.

Lerner, the co-founder and CEO of Interviewing.io, started her company after becoming frustrated by the lack of a meritocracy in software engineering. Resumes don’t tell the whole story, she found, and more candidates deserve a shot at the interview table.

Just look at Lerner’s own path. After studying brain and cognitive sciences at MIT, she decided to become a chef. “After spending some time in professional kitchens, I got exposed to how hiring in those kitchens happens, and it’s very, very different from what you might expect,” she says. “It’s extremely meritocratic. Basically, you come in in the morning with your knives, and then they teach you how to do the dishes that you’re responsible for. They also watch you chop stuff and watch you multitask, and if at the end of the night you did a good job, they hire you.”

When Lerner returned to software engineering, she soon realized it was nothing like working in a kitchen. “It wasn’t meritocratic at all,” she says. Companies fixated on where people had gone to school, or where they had worked previously, instead of what they could actually do. 

This annoyed Lerner so much that after four years working as the first female software developer at her company, she went into recruiting and eventually founded Interviewing.io, which allows people to anonymously practice their technical interview skills with senior engineers from companies like Google, Facebook, Microsoft, and more.

“Our goal is to make hiring fair and more about what you can do than how you look on paper,” Lerner says.

How They Do It

First are mock interviews, which are a bit more academic than the work software engineers do every day. If people do well in the practice interviews, they unlock interviews with real companies, bypassing the resume review altogether. 

“Let’s say you want to interview at Twitter,” Lerner says. “You can do that as early as tomorrow if you’re one of our top performers, even if you didn’t go to a top school and even if your resume doesn’t look very good. No one’s going to look at it.”

Forty percent of Interviewing.io’s top performers are nontraditional, meaning they took an alternate route to get to software engineering. Many have been rejected by a company only to be hired by the same firm after rigorous interview prep with Interviewing.io, Lerner says.

On Imposter Syndrome and Hiring Internally

Lerner is proud of the work she does, but she still struggles with an issue many women in tech face: imposter syndrome, or feeling like a fraud.

“I don’t think it ever really goes away.” she says. “What helps is one, being so busy that you don’t have time to doubt yourself. And two is repetition and proving to yourself and others that you belong. There’s no shortcut, I think.”

Lerner saw a lack of gender diversity in her time at MIT and while working at companies like TrialPay and Clicktime.com. Now that she’s CEO of her own company, she gets to set the culture for 10 employees and hundreds of contractors. 

One of the things she’s most proud of is hiring internally. “I just don’t look at resumes,” Lerner says. “Until it comes up in conversation much later, I generally don’t know what school my employees have attended. We try to interview people based on their ability, and try to make interviews very practical.” 

Source: https://www.entrepreneur.com/article/358105

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Glue raises $8 million to automate customer loyalty programs

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Loyalty automation platform Glue today raked in $8 million in series A funding from private investors led by Unicorn Technologies. The startup says that the proceeds will be put toward nudging local businesses to adopt loyalty programs.

Retail has taken a major hit during the pandemic. Total sales are expected to hit 5.7% from 2019, nearly 12% below eMarketer’s pre-pandemic estimate of $26 trillion. Some data suggests that loyalty programs could help lessen future blows. According to Accenture, loyalty program membership in the U.S. grew at a rate of 26.7% from 2012 to 2014. And one recent survey found that 50% of consumers say their primary reason for joining a loyalty program is to earn rewards on purchases.

Glue offers a platform that attempts to gauge loyalty and facilitate the development of daily, weekly, and monthly engagement plans. It self-runs rewards, coupons, and points systems and provides tools for loyalty and sales growth analysis and reporting. Glue offers purchase and behavior tracking for customer targeting and tailors reward tiers to individual businesses; it can import data from existing customer relationship management software and enable customers to register for loyalty programs on their smartphones.

“Glue started as an app creator called Bobile. At the time, we thought every business needs an app, but after a while, we understood what’s really important to the business owners we spoke with is the ability to keep their customers coming back,” Glue CEO Ira Nachtigal, who cofounded Glue with Jacob Tenenboim and Dany Gal, told VentureBeat via email. “But, they are busy.  Most local businesses don’t have the time, the knowledge, or the resources to manage it.  Loyalty, when done right, is complex, so we decided not to create yet another loyalty tool, but rather to do the work for them.”

Glue supports loyalty strategies such as points-earning systems, coupons, loyalty cards, subscriptions, prepaid multi-passes, and play-to-win games. Customers can use it to schedule holiday and special occasions greetings, launch Google Ads growth campaigns, or encourage walk-ins with geofencing campaigns.

After completing a 15-minute onboarding questionnaire on Glue’s website, business owners receive a branded members club and a projection of savings. Glue claims its programs are customized by leveraging businesses’ customer data and pairing them with data points from 100,000 organizations, resulting in what the company calls an average savings of between $15,000 to $20,000 per small business and significant revenue growth.

“Glue collects the data from thousands of businesses around the world, analyzes the consumer behavior and optimizes the loyalty strategy that is built for every business,” Nachtigal explained. “For example, let’s say you own a coffee house in Boston. Glue already has a lot of information and accumulated knowledge about coffee shops and their consumers in the east coast. Using AI Glue knows what is most likely to work for your coffee house and your customers and given your specific price range, will be able to tailor a successful loyalty strategy for your coffee house.”

Glue has a number of competitors in the space. There’s AppCard, a mobile-first loyalty marketing program for small and medium-size retailers, as well as Punchh, a startup leveraging machine learning and omnichannel integrations to create customer journeys. Just last year, Drop, a coalition customer loyalty company headquartered in Toronto, raised $44 million. That’s all to say that 15-employee Glue will have to differentiate itself from the rest of the pack, but this latest funding round — and its growing number of coffee shop, cosmetic, pet store, service provider, and car repair shop customers — suggests that it’s had success in that respect.

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Source: https://venturebeat.com/2020/11/24/glue-raises-8-million-to-automate-customer-loyalty-programs/

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Salesforce’s Einstein platform is now serving over 80 billion predictions per day

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In September 2016, Salesforce launched Einstein, an AI platform to power predictions across all of the company’s cloud-hosted products. Just over four years after Einstein’s debut, Salesforce says the platform is now delivering more than 80 billion AI-powered predictions every day, up from 6.5 billion predictions in October 2019.

Forrester Research recently wrote that companies “have to rebuild their businesses, not for today, or even next year, but to prepare to compete in an AI-driven future.” Reflecting this changing landscape, IDC expects global spending on AI to more than double to $110 billion in 2024, up from $50 billion in 2020.

Salesforce asserts that Einstein is poised to drive a substantial portion of this growth. Einstein’s predictions can include internal and customer service answers for a given use case, like when to engage with a sales lead, how likely an invoice is to be paid, and which products to recommend to bolster sales. For instance, outdoor apparel and lifestyle brand Orvis taps Einstein to develop personalized conversations with its online shoppers. Internet Creations, a business technology and consulting firm, is using Einstein to forecast long- and short-term cash flow during the pandemic. And outdoor apparel retailer Icebreaker is leveraging Einstein to suggest products for new and existing target audiences.

Beyond the top-line prediction milestone announced today, Salesforce reports a 300% increase in Einstein Bot sessions since February of this year — a 680% year-over-year increase compared to 2019. That’s in addition to a 700% increase in predictions for agent assistance and service automation and a 300% increase in daily predictions for Einstein for Commerce in Q3 2020. As for Einstein for Marketing Cloud and Einstein for Sales, email and mobile personalization predictions were up 67% in Q3, and there was a 32% increase in converting prospects to buyers using Einstein Lead Scoring.

Salesforce also says Einstein Search is fielding more than 1.5 million natural language searches per month, which works out to 1.5 natural language searches every second. It’s also delivering more than 100 million tailored keyword searches per month.

The Einstein platform is the purview of Salesforce Research, a unit previously led by former Salesforce chief scientist Richard Socher. (Socher, who joined Salesforce through the company’s acquisition of MetaMind in 2016, left in July 2020.) To train its underlying algorithms, Salesforce Research’s hundreds of data scientists draw from sources that include the anonymized content in emails, calendar events, tweets, Chatter activity, and customer data. Salesforce says innovations in Einstein arise from scientific investigations into computer vision, natural language modelstranslation, and simulation.

Einstein’s voice services recently underwent a reorganization with Salesforce’s decision to shut down Einstein Voice Assistant and Voice Skills in favor of the newly released Salesforce Anywhere app. At the time, a company spokesperson told VentureBeat that voice capabilities remained “a priority” for Salesforce and that the products it’s discontinuing will inform the development of “reimagined” functionality focused on productivity and collaboration.


Best practices for a successful AI Center of Excellence: A guide for both CoEs and business units Access here


Source: https://venturebeat.com/2020/11/24/salesforces-einstein-platform-is-now-serving-over-80-billion-predictions-per-day/

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Percepto raises $45 million for robots that inspect critical infrastructure

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Autonomous inspection solutions company Percepto today announced a $45 million round. The funds come as Percepto pivots from drone-based products to general robotics-driven inspections incorporating third-party platforms like Boston Dynamics’ Spot.

According to a report from Technavio, the inspection robot market has the potential to grow to $3.72 billion between 2020 and 2024, bolstered by industries spanning energy, oil and gas, and mining. Beyond their cost-effectiveness, robots have the ability to travel where humans can’t — either for safety or physical reasons. Machines like Spot can also be equipped with specialized hardware that delivers more detailed, consistent analytics and insights than an inspector could.

“The pandemic both highlighted and accelerated the need for many large industrial companies to consider remote autonomous data collection and autonomous analysis using our drones to mitigate some of the risk,” a Percepto spokesperson said in a statement. “[It also] highlighted the exposure of heavy industrial sites due to the reduction of on-site workforce which seriously impeded both planning and operations, significantly increasing the risk to business continuity and security.”

Percepto is the brainchild of Dor Abuhasira and Raviv Raz, who were inspired to create the company’s first product — a quadcopter dubbed Sparrow I — after returning home from a snowboarding trip with disappointing drone footage. Following a successful Indiegogo campaign, they took steps to commercialize their drone-in-a-box solution: a portable base station from which Sparrow I charges, launches, lands, syncs data with a cloud management system over LTE, and performs automated pre- and post-flight checks.

Sparrow I can be piloted on-demand or autonomously, operates during the day or night, and integrates with connected devices like “smart fences” and motion detectors to respond to alerts. The carbon fiber composite drone — which packs a rechargeable battery, 5G-compatible radios, an integral parachute, a high-resolution RGB camera, and a thermal camera — weighs about 19 pounds and can fly up to three miles round trip at speeds upwards of 46 miles per hour and a maximum height of 400 feet. It has a quoted flight time of about 38 minutes, can land in snow and rain, and is able to withstand winds of up to 150 miles per hour.

Percepto’s software leverages Sparrow I’s sensor data to track humans, vehicles, and anomalies in real time, and its orchestration dashboard enables drone pilots to define no-fly zones, free flight areas, and emergency landing zones within geofenced sites. It ties in with Percepto’s new Autonomous Inspection & Monitoring (AIM) platform, which allows customers to operate a fleet of third-party robots by deploying the most suitable machine for a task to retrieve and stream data.

For example, orchestrated through AIM, Spot carries Percepto’s sensor payload for high-resolution imaging and thermal vision to detect issues, including hot spots on machines or electrical conductors, water and steam leaks around plants, and equipment with degraded performance.

“Our autonomous robots use machine learning models to decide the best course of action in any decision point in order to carry out missions effectively and safely. For example, our Sparrow drone holds a proprietary battery usage projection model, making sure it has enough battery to complete its mission safely in changing environment conditions,” a spokesperson explained. “We use proprietary computer vision and deep learning algorithms in real time to better navigate the robots throughout missions and collect better data … [And we] use proprietary and state of the art data analysis algorithms which are focused both on general analysis, such as our changes and anomalies detection, and more case-specific analysis, which is often tailored-made using reinforcement learning techniques to match the specific needs of the site, client, or user.”

On the drone side of the equation, Percepto has rivals in H3dynamics, Skysense, and Airbotics, which are similarly developing drone-in-a-box solutions. It also competes indirectly with DJI’s Mavic 2 Enterprise, a solution tailor-made for firefighting; law enforcement; emergency response; and inspection of power lines, cell towers, and bridges. Paris-based Parrot’s recently announced Anafi Thermal is another potential rival.

But Percepto says business is steady and claims it has Fortune 500 customers in more than 10 countries, including ICL Dead Sea, Florida Power and Light (FPL), Verizon’s Skyward, and Italian electricity and gas distributor Enel. (Recurring revenue tripled in 2020 compared with 2019.) In September, Skyward gained approval from the U.S. Federal Aviation Administration that allowed pilots to fly the Sparrow drone from their homes to inspect communications infrastructure near the Big Hollow wildfire in Washington. FPL has a waiver for Sparrow flights two miles beyond the visual line of sight at one of the power utility’s 11,000-acre Florida plants, where Percepto’s drones stay above 130 feet to avoid power poles and other obstructions. And ICL Dead Sea has been operating Percepto drones to carry out inspection, safety, and security missions in its operations at the Dead Sea site.

Percepto also says it has participated in an experimental urban warfare scenario program organized by the Department of Homeland Security’s Science and Technology Directorate and the U.S. Army, which sought to test the Sparrow I’s suitability for surveillance and reconnaissance missions.

“Our customers, which include some of the world’s leading utility, oil and gas sites; mining; and other critical infrastructure facilities, are eager to fully embrace automation across their operations and reap the benefits of driving efficiency, reducing costs, and safeguarding staff. We’re excited to be the first to empower our customers with truly autonomous inspection and monitoring, driven by the management of multiple visual robotic data sources, together with other visual sources, including piloted drones, CCTV, and mobile cameras, on site or remotely,” CEO Abuhasira said, “We’re delighted that our investors have recognized the growing need in the market for autonomous inspection, which is in demand now, more than ever.”

Israel-based, 80-employee Percepto’s series B announced this week brings the six-year-old company’s total raised to $72.5 million. KDT led the round, with participation from new investors State of Mind Ventures, Atento Capital, Summit Peak Ventures, and Delek-US, along with existing investors U.S. Venture Partners, Spider Capital, and Arkin Holdings.

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Source: https://venturebeat.com/2020/11/24/percepto-raises-45-million-for-robots-that-inspect-critical-infrastructure/

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Gatik raises $25 million for autonomous short-haul delivery trucks

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Gatik, a startup developing an autonomous vehicle stack for B2B short-haul logistics, today closed a $25 million series A round. The company also announced it will bring a fleet of self-driving vans to Canada as part of a deal with Loblaw, the country’s largest retailer with over 200,000 employees.

Some experts predict the pandemic will hasten adoption of autonomous vehicles for delivery. Self-driving cars, vans, and trucks promise to minimize the risk of spreading disease by limiting driver contact. This is particularly true with regard to short-haul freight, which is experiencing a spike in volume during the outbreak. The producer price index for local truckload carriage jumped 20.4% from July to August, according to the U.S. Bureau of Labor Statistics, most likely propelled by demand for short-haul distribution from warehouses and distribution centers to ecommerce fulfillment centers and stores.

Palo Alto, California-based Gatik, which has offices in Toronto, is the brainchild of Carnegie Mellon graduate and CEO Gautam Narang. He cofounded the company in 2017 with CTO Arjun Narang and chief engineer and former Ford computer vision lead Apeksha Kumavat.

Gatik’s platform taps level 4 autonomous vehicles (capable of operating with limited human input and oversight in specific conditions and locations, as defined by the Society of Automotive Engineers) to fulfill on-demand and scheduled deliveries up to a distance of 200 miles. Its retrofitted trucks and Ford Transit 350 vans and orchestration software, which the company has been testing on public roads in California since Q1 2018, promise to transport goods around city environments more affordably.

For Loblaw, Gatik says it will transport “multi-temperature” goods and products from the retailer’s microfulfillment centers for inventory pooling across multiple locations, multiple times a day, to retail outposts across the Greater Toronto Area beginning January 2021. The program will cover five routes that will operate 12 hours a day, seven days a week.

“Gatik’s fleet of Class 1-6 autonomous vehicles moves goods from microfulfilment centers and dark stores to pick-up points like retail stores, distribution centers, and offices — known as the middle mile,” Gatik head of policy and communications Richard Steiner told VentureBeat in a recent interview. “This is critical because the middle mile is the most expensive and challenging part of the supply chain for retailers to contend with. … The key to Gatik’s success involves optimizing fixed, predetermined routes, such as those used along the supply chain’s middle mile, countless times each day. The biggest threat to the autonomous revolution is the unknown, or edge cases, which are substantially reduced on fixed journeys.”

In July, Walmart revealed that it had launched a pilot with Gatik to ferry customer orders between select store locations in Bentonville, Arkansas. Gatik’s vans transport items from a warehouse to neighborhood market stores along a two-mile route (or five-mile one-way route) in Bentonville. Each van makes up to 10 runs a day during daylight, with human backup operators behind the wheel.

More recently, Gatik received a $100,000 grant from PlanetM, a Michigan Economic Development Corporation program that seeks to fund solutions to pandemic-driven challenges in Michigan. In collaboration with an unnamed partner, referred to as “one of the state’s largest retailers,” Gatik says its autonomous trucks will operate on predetermined, fixed routes throughout Grand Rapids and Rochester.

Gatik says it will continue to target customers such as third-party logistics providers (like FedEx, UPS, and USPS), consumer goods distributors, food and beverage distributors, medical and pharmaceutical distributors, and auto parts distributors for the foreseeable future. The company has raised a total of over $29 million in venture capital. Today’s round was led by Wittington Ventures and Innovation Endeavors, with participation from FM Capital, Intact Ventures, Fontinalis Partners, Dynamo, Reilly Brennan’s Trucks VC, Intact Ventures, and AngelPad.

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Source: https://venturebeat.com/2020/11/23/gatik-raises-22-5-million-for-autonomous-short-haul-delivery-trucks/

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