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‘Get their voice out there’: How one agency entrepreneur created opportunities for other women and people of color

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‘Get their voice out there’: How one agency entrepreneur created opportunities for other women and people of color

November 18, 2021 by Michael Bürgi

Jolene Delisle started The Working Assembly in 2017 after a successful creative career that had her working at Arnold Worldwide and Instagram, among other places. While at those corporate gigs, the New Yorker felt she was too disconnected from working directly with brands — while also feeling a strong inclination toward helping other women and people of color break into the branding business. And so The Working Assembly was born.

After winning insurer Mass Mutual to redo its branding, Delisle realized there’s a market for The Working Assembly’s digital-heavy approach. Other clients, including Rent the Runway and The Guardian, soon followed. She also owns an ice-cream store in upstate New York that she’s expanding into a children’s activity center as well.

This interview has been edited for context and clarity.

How did you start The Working Assembly?

The genesis of the idea was to create a creative collective, which is why I called it The Working Assembly — because we were going to be working and then also assemble based on client needs. My background was in large-scale advertising agencies and big companies where I was leading creative teams but was more disengaged with the brand and the clients. So I wanted to have an opportunity to really work with organizations and startups that I felt had a lot of potential but could use some more hands-on creative support. I’ve been working ever since with brands at two different inflection points: an emerging brand looking to formalize and build themselves up as an established company. And then big companies who already have a big reputation but are looking to either reinvent, reimagine or reintroduce themselves to a new audience.

Does the agency get into other digital areas?

All of our projects have a digital output and a social component. We’re thinking through their digital marketing website, their landing pages, and we’re also thinking about their social content. So all of our clients that we do brand work for, we actually refresh all of their social channels as well. Because social is one of the biggest touchpoints for brands. 

I think traditionally branding agencies have been very focused on their logo and a brand book. But the reality is that if a client doesn’t have the tools or capabilities in-house to really blow out that brand book, a brand book doesn’t really become very useful. To show the elasticity of a brand through social or digital, has become actually a really big selling point for us with clients because we’re able to say, ‘Here’s assets that you can actually turn on tomorrow. And let’s also use digital as a place for us to get feedback from people and iterate on your brand.’ And so sometimes we’ll launch a brand completely using digital as an output, and then continue to iterate and refine the brand based on what’s working.

What have you done to foster better opportunities for other women looking to get into the field? 

I started the company when I did because thinking about inclusion and supporting women and minority founders become more relevant than ever. It feels very serendipitous in some ways, too, because since I started, all of our growth since has been [from] female founders and female-led companies and organizations that have organically spread the word about my company, about my services and about our offering. Very early on, I looked at the branding landscape particularly in New York and realized there’s actually a lack of agencies that are 1. led by women, and 2. led by a founder of color. And as I started networking and getting introduced to people through VCs or through clients, I realized that more and more of these founders and women wanted to work with a company that was led this way. They want to work with a values-led organization, a company that immediately had an understanding of who they were, who their demographic was, who their audience that they were reaching out to was. That’s just naturally happened, where we’ve built a very diverse and values-led organization. So much to the point now, where over half our team is identified as a person of color or identifies as a woman.

Would you say that those efforts have translated into being more on the radar of minority- or women-led brands?

I like to think that it does. And that those referrals, that network and community that we found, has really responded. But we also created something that we call TWA Labs, which essentially is a subsidized offering of what we currently offer to clients. It’s a $10K branding package that essentially helps a founder from start to fundraising. And we have helped about 20 companies raise almost $20 million. So it’s been something that we’ve been able to help a lot of founders in a very significant real tangible way: raise a lot of money, and get their message and brand out there. That’s something I’m super proud of because our whole idea is to just try to help and support more female founders, more minority founders, get their voice out there. One of the ones that’s really well known is Sanzo. It’s Asian sparkling water. We helped incubate that brand with 24-Hour Assembly. And he recently raised like $1.3 million in fundraising.

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ML-driven tech is the next breakthrough for advances in biology

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ML-driven tech is the next breakthrough for advances in biology

Image Credit: kentoh/Shutterstock

Hear from CIOs, CTOs, and other C-level and senior execs on data and AI strategies at the Future of Work Summit this January 12, 2022. Learn more


This article was contributed by  Luis Voloch, cofounder and chief technology officer at Immunai

Digital biology is in the same stage (early, exciting, and transformative) of development as the internet was back in the 90s. At the time, the concept of IP addresses was new, and being “tech-savvy” meant you knew how to use the internet. Fast-forward three decades, and today we enjoy industrialized communication on the internet without having to know anything about how it works. The internet has a mature infrastructure that the entire world benefits from.

We need to bring similar industrialization to biology. Fully tapping into its potential will help us fight devastating diseases like cancer. A16z has rephrased its famous motto of “Software is eating the world” to “Biology is eating the world.” Biology is not just a science; it’s also becoming an engineering discipline. We are getting closer to being able to ‘program biology’ for diagnostic and treatment purposes.

Integrating advanced technology like machine learning into fields such as drug discovery will make it possible to accelerate the process of digitized biology. However, to get there, there are large challenges to overcome.

Digitized biology: Swimming in oceans of data

Not so long after gigabytes of biological data was considered a lot, we expect the biological data generated over the coming years to be counted in exabytes. Working with data at these scales is a massive challenge. To face this challenge, the industry has to develop and adopt modern data management and processing practices.

The biotech industry does not yet have a mature culture of data management. Results of experiments are gathered and stored in different locations, in a variety of messy formats. This is a significant obstacle to preparing the data for machine learning training and doing analyses quickly. It can take months to prepare digitized data and biological datasets for analysis.

Advancing biological data management practices will also require standards for describing digitized biology and biological data, similar to our standards for communication protocols.

Indexing datasets in central data stores and following data management practices that have become mainstream in the software industry will make it much easier to prepare and use datasets at the scale we collectively need. For this to happen, biopharma companies will need C-suite support and widespread cultural and operational changes.

Welcome to the world of simulation

It can cost millions of dollars to run a single biological experiment. Costs of this magnitude make it prohibitive to run experiments at the scale we would need, for example, to bring true personalization to healthcare — from drug discovery to treatment planning. The only way to address this challenge is to use simulation (in-silico experiments) to augment biological experiments. This means that we need to integrate machine learning (ML) workflows into biological research as a top priority.

With the artificial intelligence industry booming and with the development of computer chips designed specifically for machine learning workloads, we will soon be able to run millions of in-silico experiments in a matter of days for the same cost that a single live experiment takes to run over a period of months.

Of course, simulated experiments suffer from a lack of fidelity relative to biological experiments. One way to overcome this is to run the in-silico experiments in vitro or in vivo to get the most interesting results. Integrating in-silico data from vitro/vivo experiments leads to a feedback loop where results of in vitro/vivo experiments become training data for future predictions, leading to increased accuracies and reduced experimental costs in the long run. Several academic groups and companies are already using such approaches and have reduced costs by 50 times.

This approach of using machine learning models to select experiments and to consistently feed experimental data to ML training should become an industry standard.

Masters of the universe

As Steve Jobs once famously said, “The people who are crazy enough to think they can change the world are the ones who do.”

The last two decades have brought epic technological advancements in genome sequencing, software development, and machine learning. All these advancements are immediately applicable to the field of biology. All of us have the chance to participate and to create products that can significantly improve conditions for humanity as a whole.

Biology needs software engineers, more infrastructure engineers, and more machine learning engineers. Without their help, it will take decades to digitize biology. The main challenge is that biology as a domain is so complex that it intimidates people. In this sense, biology reminds me of computer science in the late 80s, where developers needed to know electrical engineering in order to develop software.

For anyone in the software industry, perhaps I can suggest a different way of viewing this complexity: Think of the complexity of biology as an opportunity rather than an insurmountable challenge. Computing and software have become powerful enough to switch us into an entire new gear of biological understanding. You are the first generation of programmers to have this opportunity. Grab it with both arms.

Bring your skills, your intelligence, and your expertise to biology. Help biologists to scale the capacity of technologies like CRISPR, single-cell genomics, immunology, and cell engineering. Help discover new treatments for cancer, Alzheimer’s, and so many other conditions against which we have been powerless for millennia. Until now.

Luis Voloch is cofounder and Chief Technology Officer at Immunai

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‘Cyberpunk 2077’ next-gen upgrade will be free for PS4 and Xbox One owners

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‘Cyberpunk 2077’ next-gen upgrade will be free for PS4 and Xbox One owners

CD Projekt Red is “on track” to release the PlayStation 5 and Xbox Series X/S versions of Cyberpunk 2077 in the first quarter of 2022, the studio’s parent company announced on Monday. CDPR had initially planned to release the update in late 2021 until it announced a delay to early 2022 in October. 

CD Projekt also confirmed anyone who purchased the game on either PlayStation 4 or Xbox One will receive the next-gen update for free. Since the game is currently playable on the current generation systems through backward compatibility, everyone who owns the game on a console will get the upgrade for free. If you don’t already have Cyberpunk 2077, you can buy it while it’s currently 50 percent off on the PlayStation and Microsoft Stores and get the game at a discount before the updated version comes out next year.

All products recommended by Engadget are selected by our editorial team, independent of our parent company. Some of our stories include affiliate links. If you buy something through one of these links, we may earn an affiliate commission.

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Amazon Web Services unveils enhanced cloud vulnerability management

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Amazon Web Services unveils enhanced cloud vulnerability management

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Hear from CIOs, CTOs, and other C-level and senior execs on data and AI strategies at the Future of Work Summit this January 12, 2022. Learn more


Amazon Web Services (AWS) today announced several new features for improving and automating the management of vulnerabilities on its platform, in response to evolving security requirements in the cloud.

Newly added capabilities for the Amazon Inspector service will meet the “critical need to detect and remediate at speed” in order to secure cloud workloads, according to a post on the AWS blog, authored by developer advocate Steve Roberts. The announcement came in connection with the AWS re:Invent conference, which began today.

In a second security announcement, AWS unveiled a new secrets detector feature for its Amazon CodeGuru Reviewer tool, aimed at automatically detecting secrets such as passwords and API keys that were inadvertently committed in source code.

The security updates from AWS come as enterprises continue their accelerated shift to the cloud, even as security teams have struggled to keep up. Gartner estimates 70% of workloads will be running in public cloud within three years, up from 40% today. But a recent survey of cloud engineering professionals found that 36% of organizations suffered a serious cloud security data leak or a breach in the past 12 months.

Changing cloud security needs

In the post about the Amazon Inspector updates, Roberts acknowledged that “vulnerability management for cloud customers has changed considerably” since the service first launched in 2015. Among the new requirements are “enabling frictionless deployment at scale, support for an expanded set of resource types needing assessment, and a critical need to detect and remediate at speed,” he said in the post.

Key updates for Amazon Inspector announced today include assessment scans that are continual and automated — taking the place of manual scans that occur only periodically — along with automated resource discovery.

“Tens of thousands of vulnerabilities exist, with new ones being discovered and made public on a regular basis. With this continually growing threat, manual assessment can lead to customers being unaware of an exposure and thus potentially vulnerable between assessments,” Roberts wrote in the post.

Using the updated Amazon Inspector will enable auto discovery and begin a continual assessment of a customer’s Elastic Compute Cloud (EC2) and Amazon Elastic Container Registry-based container workloads — ultimately evaluating the customer’s security posture “even as the underlying resources change,” he wrote.

More feature updates

AWS also announced a number of other new features for Amazon Inspector, including additional support for container-based workloads, with the ability to assess workloads on both EC2 and container infrastructure; integration with AWS Organizations, enabling customers to use Amazon Inspector across all of their organization’s accounts; elimination of the standalone Amazon Inspector scanning agent, with assessment scanning now performed by the AWS Systems Manager agent (so that a separate agent doesn’t need to be installed); and enhanced risk scoring and easier identification of the most critical vulnerabilities.

A “highly contextualized” risk score can now be generated through correlation of Common Vulnerability and Exposures (CVE) metadata with factors such as network accessibility, Roberts said.

Secrets detector

Meanwhile, with the new secrets detector feature in Amazon CodeGuru Reviewer, AWS addresses the issue of developers accidentally committing secrets to source code or configuration files, including passwords, API keys, SSH keys, and access tokens.

“As many other developers facing a strict deadline, I’ve often taken shortcuts when managing and consuming secrets in my code, using plaintext environment variables or hard-coding static secrets during local development, and then inadvertently commit them,” wrote Alex Casalboni, developer advocate at AWS, in a blog post announcing the updates for CodeGuru Reviewer. “Of course, I’ve always regretted it and wished there was an automated way to detect and secure these secrets across all my repositories.”

The new capability leverages machine learning to detect hardcoded secrets during a code review process, “ultimately helping you to ensure that all new code doesn’t contain hardcoded secrets before being merged and deployed,” Casalboni wrote.

AWS re:Invent 2021 takes place today through Friday, both in-person in Las Vegas and online.

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