The BIG (but hidden) deal in the Inflation Reduction Act and other upcoming regulations

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Following the $1.2 trillion Infrastructure Investment and Jobs Act (or Bipartisan Infrastructure Law) last year, an additional $437 billion in Tuesday’s Inflation Reduction Act may seem like small change. 

It’s not.

Unless you’re into the policy details like VIA is, one thing that may have gone under the radar is that there’s the potential to add billions of dollars to consumers’ wallets and purses each year. The reason isn’t the tax credits or incentives in the bill itself (although that’s certainly part of it).

There are two different pieces of legislation and regulation that are going to make this happen. The first is this week’s Inflation Reduction Act and second is FERC 2222. The rule came out a few years ago, but won’t go into full effect until 2023. This is a national (except Texas) rule that makes it possible for pretty much anyone to participate in the wholesale energy markets. 

Wait, wholesale what?

In short, FERC 2222 says that consumers of a certain size (individually or aggregated together) can buy and sell energy at the same price that a multi-billion dollar company can. Up until now, most consumers were paid or saved whatever their going retail rate was (e.g., $0.15 to $0.30 per kWh) for reducing their consumption, shifting the time of their consumption, or selling their generation (e.g., solar) back to the grid. While not nothing, wholesale electricity rates can fluctuate dramatically. For example, during emergencies, wholesale prices can be MUCH higher (e.g., $20 per kWh). Those volatile, skyrocketing prices are becoming more frequent and lasting longer. We’ll actually be talking about the drivers of that volatility in an upcoming blog post.

The impact is that, by some estimates, a consumer could earn $500 to $1,000 (your mileage may vary) per year through various demand response programs. That’s with retail pricing. With wholesale rates, those cash payments will be significantly higher.

So that’s FERC 2222. What’s the connection to the Inflation Reduction Act?

Well, a lot of incentives are in place for consumers to upgrade to electric heat pumps, add solar, add EVs, and upgrade appliances. Anything new has the potential to be “smart.” That is, remote controlled so it can automate the process of turning on or off when needed. Like during an emergency.

The combination of new “smart equipment” purchased through the Inflation Reduction Act and FERC 2222 mean greater incentives and lower barriers to adoption (automated transactions instead of manual transactions).

If you follow the news, there’s been some backlash against the idea of having a company, like a utility, remote controlling the appliances in your home. 

We agree. That’s why we believe so strongly in our new Web3 solution, Skylight.

Three key benefits of VIA’s Skylight value proposition are:

So, overall, we’re pretty excited about the combination of events playing out right now. For savvy consumers, there’s HUGE potential for additional income and you don’t even need your tax accountant to help you out.

Of course, we’re equally excited that the regulatory direction is in line with VIA’s overall mission to make communities cleaner, safer, and more equitable.

Stay tuned for more upcoming announcements from VIA on this topic.

  1. Text – H.R.3684 – 117th Congress (2021-2022): Infrastructure Investment and Jobs Act
  2. H.R.5376 – 117th Congress (2021-2022): Inflation Reduction Act of 2022
  3. The actual amount will vary by size of home, local tariffs, local grid topology, etc. In many instances, demand response happens through an aggregator who may take as much as 90% of the savings for their role as a middle man.
  4. A demand response program is a program where electricity consumers agree to reduce their power consumption a certain number of times per contract period in return for financial compensation. A twist on this model is the Ford F-150, Duke Energy program. “Pilot incentives will reduce vehicle lease payments for program participants who lease an eligible electric vehicle (EV), including Ford F-150 Lightning trucks. In exchange, customers will allow their EVs to feed energy back to the grid – helping to balance it during peak demand.”

Transformer Tuesday: Accurately Prioritize Transformer Replacements with GDAC™

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This is the seventh installment of our blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.

Electric utilities have a hard job. They have to ensure reliability to their customers in the midst of:

With constrained budgets, rising transformer costs, and longer lead times, how can utilities ensure they accurately prioritize the right transformer replacements now and in the future?

GDAC™ provides utilities with the tools needed to precisely prioritize transformer replacement 

There is a cost effective solution that provides utilities with insights into the current and projected health of transformers at a cost any utility can afford: VIA’s Global Data Asset Collaborative™ (GDAC™).  

GDAC™ provides a secure way for utilities to pool data about their transformers (including data from measurement tests like dissolved gas analysis, oil, and furan) without compromising data privacy. By pooling data from multiple utilities, the key differentiator of GDAC™, robust quantities of data are made available for artificial intelligence (AI) to train accurate models to predict transformer health 1-10 years in advance.  

GDAC™ leverages a completely transparent Condition Based Rating (CBR) system that is based on industry standards and was co-created and validated by our founding utility partners. This gives asset managers confidence in how the rating is created and helps make it easier to interpret what to do with the results.

All of these insights are made available to asset managers in one place, in the convenience of a web-based portal. Some example reports from the GDAC™ portal that our current members love:

Utilities can use the 10-Year Condition Forecast report for a bird’s eye view of their fleet’s health, compared to other GDAC™ partners.

For more actionable granularity, GDAC™’s Highest Risk Transformers page flags individual transformers that currently have issues and are forecasted to decline over the next 3 years.

Want to accurately assess your transformers current and future condition?
Send me a note on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.

Transformer Tuesday: Anticipating EV Charging Challenges Facing Transformers

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This is the sixth installment of our blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.

For 50 years, substation transformers were built to run during the day and taper down at night to cool. Now, picture your neighborhood lined with electric vehicles (EVs). Once your neighbors end their workdays and don’t need to use their vehicles anymore, they plug their EVs in to “juice up”.

While this is convenient for EV drivers, this significantly increased demand for evening voltage places additional wear-and-tear on the electricity grid during times when transformers are used to cooling down. In this scenario, transformers stay running and can overheat or experience a malfunction (not unlike a car if you think about it).

According to a 2021 McKinsey report, U.S. EV sales increased by nearly 200% between the second quarter of 2020 and the second quarter 2021. This number is expected to rise as a result of $7.5 billion EV infrastructure funding from the Bipartisan Infrastructure Investment and Jobs Act.

Growing fleets of EVs will clearly require utilities to expand their power capacity, and therefore, optimize or add transformers to handle more intense power requirements throughout the day and evening. This leads to critical questions like: 

Which transformers should a utility repair, replace, or buy to add to their grids first?
Which units and future plans can wait?
How much will all of this cost?

Utility asset managers need to understand which transformers in their fleet are most at risk as EV penetration increases. VIA’s Global Data Asset Collaborative™ (GDAC™) can help.

Engaging with EV Stressors

Despite higher rates of EV adoption and challenges related to where and when EVs are being charged, utilities need to maintain the highest standards for electricity reliability and resiliency for their customers. GDAC™ identifies cases where transformers have unexpected declines in health condition, at an early age or in an area where previous transformer condition was consistent. These situations are good indicators to intervene sooner or review the assets in place.

Utilities analyze historical and forecasted transformer condition changes (e.g., downgrades) in locations where EV adoption is high. 

The GDAC™ portal conveniently flags high risk transformers for utilities so that they don’t have to parse through multiple databases, reports, and analyses, saving them invaluable time and effort. As a result, utilities can allocate resources to the transformers most in need, allowing them to work smarter.

As shown in the diagram to the left, utilities easily identify transformers in need of maintenance or replacement due to EV-related stressors. Utilities also glean insights from transformers located at the same substation experiencing similar EV stressors.

GDAC™ analyses like these help utility personnel with or without analysis experience to identify which transformers to repair, replace, or buy; which units and future plans can wait; and how much it will cost to address EV-related stressors.

Want to go for a ride with GDAC™?

Reach out to me via LinkedIn or email sales@solvewithvia.com to learn more about the ways GDAC™ can help you be prepared for EV-related stressors on your transformer fleet.

Values, Mission, Diversity, and … Pull Requests!

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One of VIA’s core values is: learning never goes out of style. We believe that real learning (e.g., a new instrument, a new sport, a new programming language) requires feedback from others.

At VIA, we use a common process of pull requests to review code. That is, no individual, no matter what role or how senior, can submit their code to a repo without having it first reviewed by someone else. 

But, how do you give feedback directly and also respectfully? This is an example of living two VIA values: Learning never goes out of style and Respect a challenge and challenge with respect. Balancing directness and respect is especially important in a remote working world, where an increasing portion of interactions may be virtual (e.g., on Slack), which doesn’t include any context or body language cues.

Consider the following comment: “Interesting. Why did you code this way?”

Is the commenter genuinely interested in knowing why? Is it a rhetorical question actually implying that it’s wrong? You can’t tell from the note. You also can’t guarantee how it will be interpreted by the reader.

You could provide more context, but that’s work and even then something can get misinterpreted.

So … At VIA, we use four words to help disambiguate these scenarios and save time. 

VIA VOCAB WORD MEANING
Optional “Nice! Here’s an alternative. No pressure. There are always multiple ways to solve a problem.”
Curiosity “This rocks! How did you come up with this?”
Required “Dude, this has to change.”
Future “Not right now. Let’s come back to this later.”

The result? Clear feedback, succinct communication, and no emotional damage.

This is critically important at a hugely diverse company like VIA. We have team members right out of academia, folks from industry with little academic training, folks from numerous nationalities, and 86% of our technical team speak at least one language other than English. 

“These “VIA vocab” words are meant to move us beyond seeking diversity at work to getting diversity to work. With this approach, we have a better chance of achieving the intended impact of diversity like an increased pace of innovation.”

Consistent with VIA’s mission to enable cleaner, safer, and more equitable communities, we are “open sourcing” our VIA vocab in hopes of encouraging others to make diversity work for them.

You can find a summary and example on GitHub.

Transformer Tuesday: Using GDAC™ to Learn from a Trailblazing Utility

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This is the fifth installment of our new blog series, “Transformer Tuesday,” brought to you today by VIA’s SVP, Strategic Initiatives, Joe Babiec. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.

Last week’s Transformer Tuesday post by my colleague, Will Chapman, highlighted the way GDAC™ member utilities can learn from each other’s experiences. In particular, joining GDAC™ can help a utility prepare for challenges that they haven’t yet had to solve for or frequently experienced in their own transformer fleet. This shared knowledge not only helps utilities learn from each other, but can also help save on costly transformer failures.

This week, we want to highlight the value a specific GDAC™ member, Hawaiian Electric, brings to the entire collaborative. 

Hawaiian Electric is one of GDAC™’s founding member utilities. The company serves 95% of Hawaiʻi’s 1.4 million residents on the islands of Oʻahu, Hawaiʻi Island, Maui, Lānaʻi, and Molokaʻi.

Hawaiian Electric has been referred to in the industry as a “postcard from the future.” With very high levels of distributed solar penetration, they are rapidly transforming their grid to provide 100% renewable energy by 2045. Hawaiian Electric has already accumulated considerable experience dealing with a host of unprecedented challenges related to clean energy that many in the industry will not face for several years. Utility Dive recognized Hawaiian Electric’s trailblazing efforts and named the company “Utility of the Year.”

Hawaiian Electric has been contributing valuable insights on substation transformers to the collaborative since 2019. Having their experience included in GDAC™’s many benchmarks allows other utilities to better anticipate how their transformers might behave and how long they might last, as a result of accelerating clean energy technology adoption in their service areas.

In addition to enabling valuable benchmarking, Hawaiian Electric, like other GDAC™ members, is sharing their hard-won operational insights during VIA-hosted GDAC™ workshops. Topics often include fleet management practices, plans, and challenges, as well as the future GDAC™ enhancements that would provide the most value to all utilities.

Hawaiian Electric illustrated the value of the collaborative best themselves:

“Like most electric utilities, Hawaiian Electric does its best to maximize use of grid infrastructure, some of which are nearing the end of their practical use,” said Rick Pinkerton, Director, Asset Management at Hawaiian Electric. “As we modernize our grid, we’re always looking for ways to improve our decision making. We joined GDAC™ to learn from other members and from VIA’s expertise in AI and machine learning, to improve our capabilities to prudently manage the performance, risk, and cost of our fleet of substation transformers, and other T&D assets in general.”

If you would like to learn about how GDAC™ can help your utility to “future proof” by learning from the experience of trailblazing companies like Hawaiian Electric, reach out to me on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.

Transformer Tuesday: Overcoming Barriers to Collaborative Learning

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This is the third installment of our new blog series, “Transformer Tuesday,” brought to you by VIA’s Will Chapman. In this series, we’ll address how leading utilities use VIA’s GDAC™ solution to manage their substation transformers with greater ease, insight, and cost effectiveness.

Aging electric grid components threaten the reliable, safe delivery of electricity. With substation transformer costs ranging anywhere from a few hundred thousand dollars to more than $5 million, the decision to replace these assets requires careful long-term capital investment planning. Unexpected transformer failures can upset those plans and requesting regulators to revise a utility’s rate case is not quick or guaranteed.

Here is an example of a situation that can arise when a transformer fails suddenly. If, say, Transformer 1 fails, a utility can decide to redeploy funds originally planned for the replacement of Transformer 2 into emergency purchasing of a brand new, Transformer 3. The result of this decision is that the utility needs to find a way to extend the lifespan of Transformer 2 since funds allocated to replace this transformer have gone to purchasing a new one.

So, how do utilities typically solve dilemmas like these and others?

Performing consistent maintenance is a sensible approach because aging transformers can have their lifespan extended, and it helps to defer replacement spending. To guide their maintenance work, utilities turn to predictive analytics to detect which transformers are at the greatest risk of failure. There are some helpful analytics that exist in the marketplace, however, there is a catch to predictive analytics: to be effective, they need a sufficient amount of data about transformers during normal periods of operation and leading up to faults and failure events.

Events like substation transformer failures don’t happen frequently (thankfully). But, utilities with too few failure events may not have a sufficient amount of transformer data on their own to train accurate predictive models, like Utility A on the left of the diagram below.

In principle, Utility A could address this challenge of data scarcity by exchanging data with other utilities so each utility has enough data to train and apply their predictive models and benchmarks, as shown on the chart to the right above. However, in practice, sharing sensitive operational data with other organizations presents serious privacy and security risks. Even if those risks are managed, utilities often keep their data in different or even incompatible formats. Utilities can find themselves needing so much time accessing and preparing data for analysis that they lack timely insights or have to abandon predictive analysis altogether.

VIA’s Global Data Asset Collaborative™ (GDAC™) overcomes these problems.

The Bridge to Predictive Insights

GDAC™ solves for each of the obstacles mentioned above: data scarcity, data privacy and security risks, and different data formats. With GDAC™, each utility retains complete control of its data and is able to connect to utility-controlled data locations. The collaborative does this by establishing a secure, privacy-protecting bridge between each company’s data and GDAC™ predictive analytics.

Leveraging GDAC™, utilities can prevent unanticipated transformer failures by:

  • Predicting the future lifespan of individual transformers 3 years in advance and transformer fleets 10 years in advance
  • Identifying the contributing factor(s) for health condition changes in order to take the appropriate course of action to extend the life of an asset
  • Comparing individual transformers against the collaborative benchmark to better inform maintenance and replacement planning

With GDAC™ (pictured above), utilities can forecast individual transformer health anywhere from 1 to 3 years in advance.

By using GDAC™, utilities share access to, not copies of, valuable transformer data and learn from the combined valuable experiences with faults and failures. This enables GDAC™ member utilities to reliably predict transformer failures and minimize unexpected replacement scenarios.

Want to expand your transformer knowledge base?

Reach out to me on LinkedIn or email sales@solvewithvia.com to set up some time to chat and get a free analysis of your most at risk transformers.

Open Source Monday: Zero-Knowledge Proofs

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For the third installment of our “Open Source Monday” blog series, we provide a demonstration and example code of how Zero-Knowledge Proofs can be applied to clean energy applications.

Zero-Knowledge Proofs (ZKPs) will be very familiar to blockchain experts and cryptocurrency enthusiasts. As we described last week, there are also non-financial applications for ZKPs in the clean energy sector. 

Imagine that you are an electric vehicle charging station company. You collect data from charging stations that have a huge amount of individual information. You collect and centralize that data for billing and maintenance. Some of the data could even be considered personally identifiable information. That is, time, location, vehicle type, etc. could be pieced together to identify an individual even without having a specific name of a person. 

In summary, your data is valuable. Others ask for it. The local utility wants access to help plan grid upgrades. The local government wants to use it to plan public transportation. Community groups want access to learn the impact on the environment. Do you hand over your data to them? A better approach would be to enable them to ask questions of your data in an anonymized way without you physically transferring the data. Fewer copies means less risk.

As an energy planner (e.g., utility, government, community group) how do I know the data is real if I never see it? This is where ZKPs come in. ZKPs can prove that the data is as expected without having to reveal the actual data itself. 

The video below shows an example of some of the steps to accomplish this. 

What you’ll see is:

  1. Two different “customer” datasets are provided to form a single dataset. Continuing the analogy above, this is like the EV charging station company storing two different customers’ data in the company’s database.
  2. That data is off-chain. A central Oracle creates a non-interactive proof.
  3. The Oracle also converts the proof into an image.
    The data is an array and each value in the array
    is represented by a proof in the form of a grayscale pixel.
  4. A new ZKP verification ERC721 compatible smart contract is created and an NFT of the image is minted.
  5. Using Truffle, a smart contract can be called to execute the validation of data without revealing the identity of the individual.

For our implementation, we take advantage of some recent advances in ZKPs. In particular, many ZKPs rely on some interaction with a prover and a verifier. They ask each other a series of questions to validate the data. Here, we apply an approach inspired by zk-SNARKs. The “N” in SNARK is for Non-Interactive. The genius behind this approach is that all the proof can be provided in a single message to the verifier, eliminating the traditional back and forth. There is a LOT of math behind this which is out of scope for our example. You can learn more about the math and how it works thanks to Zcash. For simplicity in this example (see GitHub), we use a simple hash implementation rather than a full zk-SNARK.

One other addition that we made here is that since the proof is a simple message, we can codify it as an image. We can then mint the image as an NFT. The big advantage of this approach is that proofs are visible to everyone and searchable by anyone on a platform like OpenSea or Coinbase without revealing any individual data. This removes a transaction headache for the data owner. They don’t need a new system or special hosting, etc. to handle inquiries about their data. 

And, the last addition, is that we have an example Polygon smart contract that enables an individual to validate their own dataset. What the validation code enables is that the EV charging company and / or energy planners who incentivize data owners to validate data get greater assurance that the data is real. This is a great use case of data privacy enabled through crypto.

The basic principles here can be applied to many sectors where there is centralized off-chain data, strict data privacy needs, and a need to prove the data is valid. Next week, you’ll see an expansion of this proof to leverage more of the zk-SNARK stack.

Mastery Monday: Why You Should Care About Zero-Knowledge Proofs

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This is the second installment of our blog series, “Mastery Monday with VIA” where we share with you some of the inside details of our technology and math in 5 minutes or less. So, are you ready to become a master?

Math impacts everything we do. You never really see the math, but you experience it.

AI is the math that helps us control our TVs with our voice and drive our Teslas. We watch Netflix and listen to Spotify, courtesy of compression algorithms that send more and more data through increasingly crowded bandwidth.

One of the invisible math innovations that is changing the world is Zero-Knowledge Proofs or ZKPs. 

If you’re not familiar with ZKPs, these videos from UCLA Professor Amit Sahai and Up and Atom do an excellent job of explaining the concept easily. We particularly like how Prof. Sahai gets a 5 year old and a 13 year old to repeat back his definition of a ZKP, after he explains it. It’s a testament to great teaching.

So, why should you care about ZKPs?

The short answer is that if you care about privacy and fairness, then you care about ZKPs. It’s the math for you.

For example, ZKPs are used every day by millions of people in bitcoin and other cryptocurrency trading. It’s how two parties who don’t know each other can verify that the right amount of funds were transferred from one to another without the need of an intermediary like a bank. There are other, non-financial uses of ZKPs, as well. 

Given VIA’s mission to enable cleaner, safer, and more equitable communities, let’s use an example from the clean energy sector. VIA blog readers will know that our software platform enables energy data to be analyzed in such a way that an analyst will never see the source data (read more about that here).

This has obvious data privacy benefits to the data owner. Data owners don’t have to physically transfer their data to anyone or let an analyst see it in any way.

But, what about the analysts? How do they know that the data is legit? 

Well, one way is that an analyst could just trust the data owner. That works well if you both know the data owner and believe that they are reputable. For example, if you know the data owner is your public utility, and trust them, then as an analyst, you may say, “the data must be OK.”

What if the data owner isn’t someone you trust? They don’t necessarily have to be “untrustworthy.” You just don’t know them. So, the new energy retailer in your neighborhood, or the EV charging station start-up, or the microgrid operator may be perfectly legitimate. But, how do you know? How can you make sure they are playing fair?

This is where ZKPs come in. You don’t have to know. You don’t have to trust them. With ZKPs, you can mathematically verify that the data stored by the utility corresponds to the data offered to the analyst. Also, ZKPs, given a verifier, enable us to validate that the values of the data provided by the utility are indeed what the verifier is expecting. 

To take the example even further, think about consumer data. Energy is decentralizing rapidly to the individual level (e.g., rooftop solar and EVs). Your energy data is literally personally identifiable information so data privacy is paramount. At the same, you can’t possibly know and trust every other individual consumer as a data owner. ZKPs can address this.

So, is there a ZKP for energy data that energy analysts can use? Stay tuned for next week’s post …

 

Open Source Monday: Homomorphic Encryption Meets NFT

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For the second installment of our “Open Source Monday” blog series, we are offering up a smart contract-based homomorphic encryption example. Check it out below!

Since you’re reading today’s blog, we’re betting you’ll have seen the fun math video we shared last week explaining how homomorphic encryption (HE) works. And, if you’re a long-time VIA follower, you will recall that we first released our own HE library back in 2020*.

Moving from math to code, here is an example of how to use the library using a smart contract. The great thing about this particular example is that you can use a standard ERC-1155 token. 

In summary, here’s what you’ll see:

  1. Two NFTs (bird images) that have one encrypted number each in their metadata.
    a. The NFTs are hosted on IPFS and searchable on OpenSea.
    b. The metadata also includes the public key and a sequence of coordinates on an elliptical curve.
    c. VIA uses NIST-compliant, 2048-bit RSA equivalent, elliptic curve cryptography (ECC).
  2. Polygon is used to create a standard ERC-1155 contract and mint all NFTs. The sum of the encrypted number NFT is represented as a third image (an egg).
  3. For this example, a Polygon scanner was used to enter the encrypted numbers and then sum them with VIA’s HE library. NOTE: In a live setting we would use an Oracle to execute the computation programmatically. 
  4. The encrypted sum gets placed in the metadata of a new NFT and minted. 
  5. The sum can be decrypted by the private key owner as verified by an Oracle.

OpenSea has the NFTs with encrypted data. For everyone’s reference, here are the unencrypted NFTs.

Of course, NFTs don’t have to be the source of the addition. This illustration, however, should resonate with Web3 game designers and NFT minters alike. For example, you could offer treasury chest NFTs based on breeding and only provide the reward, decrypted value, to the owner of the NFT.

You can also substitute another HE library, other than VIA’s, if you prefer. The VIA library has a number of advantages that we described in our original 2020 post.

Some of the key advantages of VIA’s HE library include:

  • NIST-compliant ECC
  • No limit on digits for addition
  • Fixed point calculations
  • Benchmarked as significantly faster than many other HE libraries

Reach out if you’d like to learn more about the VIA library.

Weigh in!

We’re considering hosting an Oracle to enable this functionality in general for anyone on a public blockchain. Would this be of interest to you? If so, Support this post (via LinkedIn) and RT (via Twitter).

*As one update to the 2020 HE post, VIA was issued patents on its homomorphic encryption approach in 2021 and additional patents in February 2022.

Mastery Monday: Homomorphic Encryption

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This is the first installment of our blog series, “Mastery Monday with VIA” where we share with you some of the inside details of our technology and math in 5 minutes or less. So, are you ready to become a master?

So, what is homomorphic encryption (HE)? 

HE is a way to compute something without knowing what the numbers are (i.e., keeping them encrypted). For example, adding two numbers or multiplying two numbers and learning the exact result while keeping each of the two input numbers secret.

Why does it matter? 

Unencrypted data is unsafe. With cybersecurity increasing, the last remaining case where data routinely remains unencrypted is during computations. Encryption is already commonly used when data is stored and when it’s sent from one place to another. 

When would you use it? 

Anytime you use math. Which is everywhere. A simple example is a census. I want to know how many people live in a town without knowing how many people live on any single street, in a particular building, or in their own home. AI is all math. So, voice and face recognition while the data is private is a more complicated example.

How does it work?

Check out this less than 4 minute video below! 

Please note: this video was filmed in VIA’s new office space, hence considerable echo. We recommend using the closed captions.

Want to learn more?

VIA holds several issued patents in homomorphic encryption. 

Other details related to VIA’s approach to HE are available from VIA’s earlier blog from 2020.

Next week, we’ll be sharing some code and a use for HE.

 

Below is a transcript of the “Homomorphic Encryption Explained” video.

Everybody, everywhere is asking about homomorphic encryption.

Said no one ever.

It’s not actually a thing that anyone ever asks about, but it’s super important, nonetheless.

And the reason is because keeping our data safe is super important.

So, the idea that we keep data safe when it’s at rest – that happens. Where the data is not safe is when you actually try to do some math on numbers.

For example, you have some data or information [Becky] and you have some data or information [Sam] and you want to do a comparison.

So, both of you have kitten collectible porcelain statues. And now we want to know which one of you has more without either of you revealing your own number because your porcelain kitten collection data is intensely personal.

[Becky] How did you know? 

[Sam] True.

As a person who’s doing, you know, high academic research, I’m really interested in the total sum of kitty collectors in this world and how many porcelain kitties there are in the world. That’s my thing! I’m super interested in it.

Don’t judge me.

Okay, so here’s what we’re going to do. We’re going to now add up the number of porcelain kitties in your collection [Becky] and the number of porcelain kitties in your collection [Sam]. And Becky, you’re not going to tell Sam how many. And Sam, you’re not going to tell Becky. And neither of you are going to tell me. And, even so, as a world-class researcher, I am going to be able to tell how many there are in the world without knowing either of those things.

And that’s one definition of homomorphic encryption, which is the ability to add up or multiply or divide or subtract or be able do some math without ever actually revealing any individual number.

So, the way that we are going to do that is we’re going to pretend this is my homomorphic encryption specialist device.

It’s actually my calculator on my phone here.

And as an example, what I’m going to do first is type in a number that is only visible to me, the researcher. And to you, the audience, only. So just let’s keep it between us. 

And now, I’m going to pass this to Becky. Add to whatever number I sent you. I want you to type it in and add the number of porcelain kitties that are in your collection.

Now you’re going to pass that to Sam.

Sam, I want you to add how many are in your collection.

Ok, now you’re going to pass it back to me.

And just to be clear, Becky, do you know how many porcelain kitties Sam has?

[Becky] No idea.

[Sam] Do you know how many porcelain kitties Becky has? (shakes head)

And, I don’t know how many they have either individually but I do know that together we have 24 is my guess. But is that true? That’s what I have in my calculator. Let’s see.

Becky, how many were in your collection actually? 

[Becky] 8.

And how many were in your collection?

[Sam] 16.

So 8 and 16, I’m pretty sure is 24. So we got the number! Even though neither of you knew each other’s numbers and I didn’t know what your numbers were.

And, there’s a lot of things you can do together to continue to obfuscate and hide the original numbers.

And we’ll talk later about some use cases.

We have an upcoming piece just on a use case of homomorphic encryption and NFTs in gaming. So, we’ll look forward to sharing some code and why that may be useful next time.

But, here was a little bit of a theory of homomorphic encryption particularly applied to addition.

Thanks for watching!

Open Source Monday: How to Spot Malware in Your NFT

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Like the internet and GPS that we use every day, VIA’s data privacy and security platform was first tested at scale by the U.S. Department of Defense.

A major U.S. intelligence agency has been actively testing the ability of VIA’s blockchain platform to detect potential cyber threats to data sources. 

We can’t disclose much that we did in detail. Actually, we can’t disclose anything in detail. After six months and well over 350 tests, there is one insight, however, that we feel is important to share publicly:

It’s ridiculously easy to inject malware into a file that can then be downloaded as an NFT!

As NFTs have exploded in popularity (23% of millennials in the U.S. collect them), adding malware to an NFT is an easy and fast way for malicious users to spread chaos.

So, today, VIA is making a malware check for NFTs code available for free, for anyone: https://github.com/viascience/nftscan. Special thanks to the steganography open source community for their help to create this NFT vulnerability scanner.

This initial version on GitHub has three separate malware checks. There are instructions on how to submit a pull request for you to add your own additional malware checks. If you’re interested in using the code on your website, write to us at info@solvewithvia.com. 

Want to learn more about how hidden text and malware code can be easily transferred when not checked? Watch this 43 second video.

If you’re interested in making the NFT community safer, please share this blog with your networks!

Stay safe out there everyone!

Why Switzerland?

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Yes, we love chocolate, cheese, and clean mountain air.
That (alone), however, is not why VIA is spending so much time in Switzerland.
Switzerland is the leader in three areas core to VIA: clean energy, data privacy, and blockchain.

Clean Energy

More than 190 countries around the world have pledged to reduce carbon emissions. Switzerland is one of the few that has legislation, a deadline, and active programs to move towards net zero. Not only is this commitment aligned with VIA’s mission, it enables VIA to actively support the clean energy transition and exactly where that transition is happening the fastest. As part of VIA’s commitment to energy and Switzerland, we’re pleased to have been admitted to the Association of Swiss Electrical Companies last week.

Data Privacy 

Arguably no country in the world has a stronger reputation for data privacy than Switzerland. The laws around data privacy continue to evolve and become stricter over time. By being aware of the leading edge of privacy regulations, VIA’s platform is in a position to support any jurisdiction.

Blockchain

Switzerland’s Crypto Valley is to blockchain what Silicon Valley is to software. With over 1,000 blockchain companies and one of the world’s first countries to enact crypto and blockchain legislation, Switzerland is an ideal location to lead blockchain initiatives. Earlier this year, VIA was admitted to the Swiss Blockchain Federation (see photo below). It’s in everyone’s interest to participate in an active innovation community that also has a clear regulatory framework.

Pictured above at the general assembly of the Swiss Blockchain Federation in Zurich: Ray Neubauer, Expansion Manager at VIA, Markus Riner, Head of Digitalization at VSE (Swiss Association of Electricity Suppliers), and Dr. Fabian Streiff, Head of Economic Development Agency of the Canton of Zurich.

If you’re interested in hearing more about how and why we chose Switzerland as our European headquarters, you can watch this ten minute video with our CEO, Colin Gounden being interviewed by the Swiss Ambassador to the U.S.

The End of Pilot Purgatory

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We’re excited to have Andrew Bright, former ABB executive and VIA’s advisor to our Swiss office, contribute to our blog. Read on to hear his commentary on VIA’s GDAC™ Transformers: 3-Minute Pilot, which was recently upgraded to maximize the value of transformer data while minimizing time.

Many industrial digitalization projects suffer from “Pilot Purgatory.” The pilots seemingly take forever and never end because no one can decide if they are a success or a failure. Since the term Pilot Purgatory was first coined a few years ago, much has been written about how to avoid it. However, the vast majority of this advice seems to involve throwing more resources, money and scale at the pilot, until well it no longer looks like a pilot but a full-scale roll-out. The logic is clear if the monthly cost of a pilot project is high enough – no one can afford to let the pilot continue indefinitely. How refreshing then, that VIA has come up with a radically different and frankly opposing approach for avoiding Pilot Purgatory.

Their new GDAC™ Transformers: 3-Minute Pilot takes just 3 minutes to complete once data is gathered. If this were a recipe, you would be allowed up to 27 minutes to source the ingredients and just 3 minutes to do the cooking. Resources, time and money are all minimized. After this experience, VIA hopes to have delivered a valuable summary of the health of one of your transformers. If this has proved insightful, the pilot has been a success, if not then GDAC™ may not be for you. Either way, the pilot will have been concluded.

With their 3-Minute Pilot, VIA aims to demonstrate three specific concepts:

  1. show valuable insights about the health of one transformer and that the math really works;
  2. show that valuable analysis can be conducted whilst keeping data private and confidential; and
  3. provide an educational component about how VIA does what it does. VIA does more than provide recommendations, it also explains why & how a particular recommendation was made.

All three of these components are embedded in the 3-Minute Pilot. If you are interested in performing a full fleet analysis going back say 20 years, that’s more of a project and not the goal of this pilot. VIA’s 3-Minute Pilot is true to the spirit and literal about the term “proof-of-concept.” This seems to be an industry first and given the simplicity and radical reduction in resources, I hope that it becomes an industry standard approach.

VIA note:

If you are interested in learning more about VIA’s GDAC™ Transformers: 3-Minute Pilot and perhaps want to give it a try, feel free to contact us.

VIA’s 3-Minute Pilot provides valuable insights on the health of transformers in just 3 minutes.

 

End of Year Reflection
Company

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As this year comes to a close, we are taking our readers on a journey through 2021 in this 3-part reflection series written by VIA’s co-founders. The series covers the incredible milestones VIA has achieved in laying the foundation for big things ahead in 2022 as we Scale Up!

If any of you are Ted Lasso fans, you’ll know the philosophy that he lives by, “It’s not about winning or losing. It’s about being the very best versions of ourselves that we can be.” This year we definitely had our share of ups and downs. I, personally, am most proud of the positive attitude and resilience that our VIAneers demonstrated this year. Of course, it doesn’t hurt to win too!

This year VIA turned five. It seems like the perfect time to review in “ABC format” a few of our company wins. For D and E, see the blogs of VIA’s CSO, Jeremy Taylor, to learn more about the technical Distance we covered this year and COO, Kate Ravanis, to learn about Employee related milestones. 

A is for Series A. Earlier this year, VIA closed our $10M Series A equity financing round. While cash is always good, we’re privileged to have what we consider to be the premier clean energy fund in North America to lead the round. We also had one of the top 3 largest Silicon Valley-based B2B software companies in the world co-invest. We think quality begets quality. It’s an honor to have this level of support and growth capital to continue to scale VIA. You’ll see investments in our people and technology as we continue to keep up with increased customer demand.

B is for Buildings (and infrastructure). Our mission is to enable cleaner, safer, more equitable communities. Buildings and infrastructure are clearly the biggest physical components of our communities. While infrastructure was in the headlines for almost the entirety of 2021, this is a sector where VIA started to gain traction last year. In 2020, we won a significant contract to support the efficiency and improve the quality of life of a community of 800 buildings by analyzing and monitoring daily the 15,000 associated subsystems (utilities, HVAC, etc.). That expanded this year and in 2022 you’ll see a ten-fold increase in the number of buildings and other critical infrastructure that we support.

C is for Customers. VIA’s customers doubled in 2021 and we are on track to double again in 2022. For our critical infrastructure application, JARVIS™, we were able to add Tyndall Air Force Base in Florida as a customer and in December have a new multi-million dollar award that we will announce fully in January. 

It’s also the most positive endorsement of our value that two of our power customers have not only renewed their contracts but grown from an annual commitment to a three year contract. You’ll see new announcements in the first quarter of 2022 regarding our work with the U.S. Space Force. For obvious reasons, you won’t see anything about work that we won recently with a U.S. intelligence agency. Those are also both great endorsements of VIA’s value proposition: data analytics that’s cyber secure and privacy protected.

This past year was really a breakthrough year from a people, technology, and customer perspective. 2022 will be all about building on that base and continuing to scale. In the meantime, thank you all for your support in creating the solid foundation that VIA has laid. We sincerely wish all of you the very best to you and yours for 2022.

 

End of Year Reflection
Research and Technology

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As this year comes to a close, we are taking our readers on a journey through 2021 in this three-part reflection series written by a variety of VIA’s leaders. The series covers the incredible milestones VIA has achieved in laying the foundation for big things ahead in 2022 as we Scale Up!

In 2021, VIA began to harvest some of the fruits of our research and previous development efforts of years past. We’re proud to share with you our technology accomplishments and what will make 2022 another record breaking year.

Technology Platform: Security and Agility

2021 was a year filled with major accomplishments for our technology platform.

Our VP Architecture, Jesus Cardenes, along with the entire DevSecOps team, pioneered a number of significant security enhancements to our data privacy-preserving analytics platform,  TAC™. In 2020, we released the capability to run TAC™ in a multi-cloud environment and continued to enhance these capabilities this year. In 2021, thanks to a robust container hardening pipeline, VIA celebrated having the first U.S. Department of Defense-wide cybersecurity accredited blockchain application. As part of our cybersecurity accreditation, we ensured that we migrated TAC™ to a Zero Trust Architecture and implemented Least Privilege Principle cybersecurity practices throughout our full product suite.

This year, TAC™ scaled as an application platform and currently supports multiple distinct analytics capabilities. Technical Architect, Ashley DaSilva, and her team put the TAC™ Ingestion Engine into production. This enables applications to orchestrate complex data ingestion and transformation workflows like taking thousands of files and automating their wrangling into an AI-ready database format. Early in 2021, execution auditability was demonstrated by our Technical Architect, John Muddle and his team, and was further developed by fellow Technical Architect, Madjid Aoudia, and his team demonstrating a highly scalable and auditable analytics system for satellite image data. These new features are key enablers for VIA’s full solution range, including VIA Insights Market™, GDAC™ Transformers, SWEET™, and JARVIS™.

There’s a Patent for That

In 2021, we were proud to have been granted our first patents developed by our VP Engineering, Kai Cheung, and fellow collaborators. These initial patents protect innovative technologies for homomorphic encryption and machine learning model evaluation. We also filed three new patents, ranging in scope from encrypted search, decentralized aggregation, and workflow threat mitigation. This brings VIA to a total of more than ten pending patents. We look forward to positive news on several of these filings in 2022. These technologies make TAC™ more secure, improve model execution performance, and lower power consumption. You’ll hear more about our efforts to reduce the carbon intensity of AI in 2022.

Research: Setting the Stage for Big Things

In 2020, we began work with our university research partner HSLU, smart meter manufacturer Landis+Gyr, and the Swiss Federal office of Energy. We finalized our first use cases that will help Distribution System Operators (DSOs) understand how technologies like electric vehicles, solar power generation, and battery storage are driving changes in the Swiss power system. In 2021, the team developed novel privacy-preserving algorithms to detect congestion in power systems, and completed a study of federated learning and model personalization for improved energy consumption forecasting. These technologies are being deployed at the edge, directly on smart meters and will be field tested in the first half of 2022. 

In 2022, we look forward to the start of a research collaboration with the University of British Columbia (UBC) on demand response for grid stabilization. The project will include the development and testing of blockchain-based algorithms for coordination between distributed energy resources across multiple distribution feeders. At VIA, we see this project as the start for a number of avenues of research collaboration into data-driven and privacy-preserving AI solutions for power system stabilization.

With all of our technology advancements in 2021, we were able to meet the needs of our customers, accept prestigious awards, and set the foundation to scale in 2022. The last blog in this series will highlight these major milestones we achieved as a company this year.