Sep
17
2020
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Perigee infrastructure security solution from former NSA employee moves into public beta

Perigee founder Mollie Breen used to work for NSA where she built a security solution to help protect the agency’s critical infrastructure. She spent the last two years at Harvard Business School talking to Chief Information Security Officers (CISOs) and fine-tuning that idea she started at NSA into a commercial product.

Today, the solution that she built moves into public beta and will compete at TechCrunch Disrupt Battlefield with other startups for $100,000 and the Disrupt Cup.

Perigree helps protect things like heating and cooling systems or elevators that may lack patches or true security, yet are connected to the network in a very real way. It learns what normal behavior looks like from an operations system when it interacts with the network, such as what systems it interacts with and which individual employees tend to access it. It can then determine when something seems awry and stop an anomalous activity before it reaches the network. Without a solution like the one Breen has built, these systems would be vulnerable to attack.

Perigee is a cloud-based platform that creates a custom firewall for every device on your network,” Breen told TechCrunch. “It learns each device’s unique behavior, the quirks of its operational environment and how it interacts with other devices to prevent malicious and abnormal usage while providing analytics to boost performance.”

Perigee HVAC fan dashboard view

Image Credits: Perigee

One of the key aspects of her solution is that it doesn’t require an agent, a small piece of software on the device, to make it work. Breen says this is especially important since that approach doesn’t scale across thousands of devices and can also introduce bugs from the agent itself. What’s more, it can use up precious resources on these devices if they can even support a software agent.

“Our sweet spot is that we can protect those thousands of devices by learning those nuances and we can do that really quickly, scaling up to thousands of devices with our generalized model because we take this agentless-based approach,” she said.

By creating these custom firewalls, her company is able to place security in front of the device preventing a hacker from using it as a vehicle to get on the network.

“One thing that makes us fundamentally different from other companies out there is that we sit in front of all of these devices as a shield,” she said. That essentially stops an attack before it reaches the device.

While Breen acknowledges that her approach can add a small bit of latency, it’s a tradeoff that CISOs have told her they are willing to make to protect these kinds of operational systems from possible attacks. Her system is also providing real-time status updates on how these devices are operating, giving them centralized device visibility. If there are issues found, the software recommends corrective action.

It’s still very early for her company, which Breen founded last year. She has raised an undisclosed amount of pre-seed capital. While Perigee is pre-revenue with just one employee, she is looking to add paying customers and begin growing the company as she moves into a wider public beta.

Sep
16
2020
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Luther.AI is a new AI tool that acts like Google for personal conversations

When it comes to pop culture, a company executive or history questions, most of us use Google as a memory crutch to recall information we can’t always keep in our heads, but Google can’t help you remember the name of your client’s spouse or the great idea you came up with at a meeting the other day.

Enter Luther.AI, which purports to be Google for your memory by capturing and transcribing audio recordings, while using AI to deliver the right information from your virtual memory bank in the moment of another online conversation or via search.

The company is releasing an initial browser-based version of their product this week at TechCrunch Disrupt where it’s competing for the $100,000 prize at TechCrunch Disrupt Battlefield.

Luther.AI’s founders say the company is built on the premise that human memory is fallible, and that weakness limits our individual intelligence. The idea behind Luther.AI is to provide a tool to retain, recall and even augment our own brains.

It’s a tall order, but the company’s founders believe it’s possible through the growing power of artificial intelligence and other technologies.

“It’s made possible through a convergence of neuroscience, NLP and blockchain to deliver seamless in-the-moment recall. GPT-3 is built on the memories of the public internet, while Luther is built on the memories of your private self,” company founder and CEO Suman Kanuganti told TechCrunch.

It starts by recording your interactions throughout the day. For starters, that will be online meetings in a browser, as we find ourselves in a time where that is the way we interact most often. Over time though, they envision a high-quality 5G recording device you wear throughout your day at work and capture your interactions.

If that is worrisome to you from a privacy perspective, Luther is building in a few safeguards starting with high-end encryption. Further, you can only save other parties’ parts of a conversation with their explicit permission. “Technologically, we make users the owner of what they are speaking. So for example, if you and I are having a conversation in the physical world unless you provide explicit permission, your memories are not shared from this particular conversation with me,” Kanuganti explained.

Finally, each person owns their own data in Luther and nobody else can access or use these conversations either from Luther or any other individual. They will eventually enforce this ownership using blockchain technology, although Kanuganti says that will be added in a future version of the product.

Luther.ai search results recalling what person said at meeting the other day about customer feedback.

Image Credits: Luther.ai

Kanuganti says the true power of the product won’t be realized with a few individuals using the product inside a company, but in the network effect of having dozens or hundreds of people using it, even though it will have utility even for an individual to help with memory recall, he said.

While they are releasing the browser-based product this week, they will eventually have a stand-alone app, and can also envision other applications taking advantage of the technology in the future via an API where developers can build Luther functionality into other apps.

The company was founded at the beginning of this year by Kanuganti and three co-founders including CTO Sharon Zhang, design director Kristie Kaiser and scientist Marc Ettlinger . It has raised $500,000 and currently has 14 employees including the founders.

Sep
15
2020
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Latent AI makes edge AI workloads more efficient

Latent AI, a startup that was spun out of SRI International, makes it easier to run AI workloads at the edge by dynamically managing workloads as necessary.

Using its proprietary compression and compilation process, Latent AI promises to compress library files by 10x and run them with 5x lower latency than other systems, all while using less power thanks to its new adaptive AI technology, which the company is launching as part of its appearance in the TechCrunch Disrupt Battlefield competition today.

Founded by CEO Jags Kandasamy and CTO Sek Chai, the company has already raised a $6.5 million seed round led by Steve Jurvetson of Future Ventures and followed by Autotech Ventures .

Before starting Latent AI, Kandasamy sold his previous startup OtoSense to Analog Devices (in addition to managing HPE Mid-Market Security business before that). OtoSense used data from sound and vibration sensors for predictive maintenance use cases. Before its sale, the company worked with the likes of Delta Airlines and Airbus.

Image Credits: Latent AI

In some ways, Latent AI picks up some of this work and marries it with IP from SRI International .

“With OtoSense, I had already done some edge work,” Kandasamy said. “We had moved the audio recognition part out of the cloud. We did the learning in the cloud, but the recognition was done in the edge device and we had to convert quickly and get it down. Our bill in the first few months made us move that way. You couldn’t be streaming data over LTE or 3G for too long.”

At SRI, Chai worked on a project that looked at how to best manage power for flying objects where, if you have a single source of power, the system could intelligently allocate resources for either powering the flight or running the onboard compute workloads, mostly for surveillance, and then switch between them as needed. Most of the time, in a surveillance use case, nothing happens. And while that’s the case, you don’t need to compute every frame you see.

“We took that and we made it into a tool and a platform so that you can apply it to all sorts of use cases, from voice to vision to segmentation to time series stuff,” Kandasamy explained.

What’s important to note here is that the company offers the various components of what it calls the Latent AI Efficient Inference Platform (LEIP) as standalone modules or as a fully integrated system. The compressor and compiler are the first two of these and what the company is launching today is LEIP Adapt, the part of the system that manages the dynamic AI workloads Kandasamy described above.

Image Credits: Latent AI

In practical terms, the use case for LEIP Adapt is that your battery-powered smart doorbell, for example, can run in a low-powered mode for a long time, waiting for something to happen. Then, when somebody arrives at your door, the camera wakes up to run a larger model — maybe even on the doorbell’s base station that is plugged into power — to do image recognition. And if a whole group of people arrives at ones (which isn’t likely right now, but maybe next year, after the pandemic is under control), the system can offload the workload to the cloud as needed.

Kandasamy tells me that the interest in the technology has been “tremendous.” Given his previous experience and the network of SRI International, it’s maybe no surprise that Latent AI is getting a lot of interest from the automotive industry, but Kandasamy also noted that the company is working with consumer companies, including a camera and a hearing aid maker.

The company is also working with a major telco company that is looking at Latent AI as part of its AI orchestration platform and a large CDN provider to help them run AI workloads on a JavaScript backend.

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