May
15
2018
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Veridium Labs teams with IBM and Stellar on carbon credit blockchain

Veridium Labs has been trying to solve a hard problem about how to trade carbon offset credits in an open market. The trouble is that more complex credits don’t have a simple value like a stock, and there hasn’t been a formula to determine their individual value. That has made accounting for them and selling them on open exchanges difficult or impossible. It’s a problem Veridium believes they can finally solve with tokens and the blockchain.

This week the company announced a partnership with IBM to sell carbon offset tokens on the Stellar blockchain. Each company has a role here with Veridium setting up the structure and determining the value formula. Stellar acts as the digital ledger for the transactions and IBM will handle the nuts and bolts of the trade activity of buying, selling and managing the tokens.

Todd Lemons, CEO and cofounder of Veridium Labs, which is part of a larger environmental company called EnVision Corporation, says that even companies with the best of intentions have struggled with how to account for the complex carbon credits. There are simpler offset credits that are sold on exchanges, but ones that seek to measure the impact of a product through the entire supply chain are much more difficult to determine.  As one example, how does a company making a candy bar source its cocoa and sugar. It’s not always easy to determine through a web of suppliers and sellers.

Moving forward

To partly solve this problem, another Envision company, InfiniteEARTH developed a way to account for them called the Redd+ forest carbon accounting methodology. It is widely accepted to the point that it has been incorporated in the Paris Climate Agreement, but it doesn’t provide a way to turn the credits into what are called fungible assets, that is an easily tradable one. The problem is the value of a given credit shifts according to the overall environmental impact of producing a good and getting it to market. That value can change according to the product.

Jared Klee, blockchain manager for token initiatives at IBM, says that buying and accounting for Redd+ credits on the company balance sheet has been a huge challenge for organizations. “It’s a major pain point. Today Redd+ credits are over the counter assets and there is no central exchange,” he said. That means they are essentially one-off transactions and the company is forced to hold these assets on the books with no easy way to account for their actual value. That often results in a big loss, he says, and companies are looking for ways to comply in a more cost-efficient way.

Putting it together

The three companies — Veridium, IBM and Stellar — have come together to solve this problem by creating a digital token that acts as a layer on top of the carbon credit to give it a value and make it easier to account for. In addition, the tokens can be bought and sold on the blockchain.

The blockchain provides all the usual advantages of a decentralized record keeping system, immutable records and encrypted transactions.

Veridium is working on the underlying formula for token valuation that measures “carbon density per dollar times product group,” Lemons explained. “That can be coded into a token and carried out automatically,” he added. They are working with various world bodies like the United Nations and The World Resource Institute to help figure out the values for each product group.

All of the details are still being worked out as the idea works its way through the various regulatory bodies, but the companies hope to be making the tokens available for sale some time later this year.

Ultimately this is about finding ways to help businesses comply with environmental initiatives and remove some of the complexity inherent in that process today. “We hope the tokens will provide less friction and a much higher adoption rate,” Lemons said.

Apr
26
2018
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IBM introduces a blockchain to verify the jewelry supply chain

Every time I talk to someone about the viability of blockchain, I get challenged to show a real project beyond the obvious bitcoin use case. IBM has been working to build large enterprise projects blockchain and today they offered an irrefutable example that they have dubbed TrustChain, a blockchain that proves the provenance of jewelry by following the supply chain from mine to store.

As you might expect the TrustChain is built on IBM blockchain technology and includes a consortium of companies involved in every step of the supply chain: Asahi Refining, the precious metals refiner; Helzberg Diamonds, a U.S. jewelry retailer; LeachGarner, a precious metals supplier and The Richline Group, a global jewelry manufacturer. It even includes some third-party verification with UL Labs for the skeptical among you.

“What we are announcing and bringing forward has been in the works for some time. It’s the first end-to-end industry capability on blockchain that has its core in trust,” Jason Kelley, the GM of blockchain services at IBM told TechCrunch.

While there are trust mechanisms in place to ensure the authenticity of jewelry, they tend to be more piecemeal and this one is designed to be more comprehensive. One of the primary benefits of using blockchain in this instance is that it’s so much more efficient. Instead shuffling paper, the process becomes much more digital and reduces a lot (although not all) of the manual paper-pushing along the way.

Photo: IBM

Of course, just because it’s on the blockchain doesn’t mean there won’t be attempts to circumvent the system, but the TrustChain has a mechanism for participants to check the validity of each transaction, each step of the way. “If there is a dispute, instead of calling and following back through the process in a more manual way, you can click on a trusted chain, and you’re able to see what happened immediately. That reduces the number of steps in the process, and speeds up what has been a paper-laden and manual effort,” Kelley explained.

He fully recognizes the hype surrounding blockchain and that it’s the latest shiny tech thing, but he says if you set aside the name, the capability is really what’s important here. “Now we can share this [data] in a permissioned network and we can be sure it’s accurate,” he said.

The notion of the permissioned blockchain is an important one here. It means that you have to be allowed on the blockchain to participate, and everyone on the blockchain has to agree to let any members on. “That’s what exciting with TrustChain. Each point in the supply chain has bought into the consortium,” he said.

He acknowledges that errors could be introduced in any system, whether intentional or not, but he says the beauty of this system is that blockchain is a team sport and many, many eyeballs are acting as a check for each step along the way. If a problem is found, it can be fixed through the same level of consensus.

Blockchain network Photo: Zapp2Photo

Kelley says this level of trust is increasingly essential because consumers are demanding transparency in the jewelry they buy. They want to be sure the diamond or precious metal in the jewelry was not mined by exploited labor and in a sustainable way. Research has found consumers are willing to pay more for such proof.

By next year, you could be able to pull out your smart phone, scan a QR code on the diamond you want to by and see a visual of the entire supply chain right on your smartphone. Kelley such an interface is in the works for the consumer side.

The blockchain is clearly still in early days, and it can’t solve every problem, but systems like this could help prove that there are actual viable scalable use cases for it.

Mar
22
2018
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IBM can’t stop milking the Watson brand

More than seven years after IBM Watson beat a couple of human Jeopardy! champions, the company has continued to make hay with the brand. Watson, at its core, is simply an artificial intelligence engine and while that’s not trivial by any means, neither is it the personified intelligence that their TV commercials would have the less technically savvy believe.

These commercials contribute to this unrealistic idea that humans can talk to machines in this natural fashion. You’ve probably seen some. They show this symbol talking to humans in a robotic voice explaining its capabilities. Some of the humans include Bob Dylan, Serena Williams and Stephen King.

In spite of devices like Alexa and Google Home, we certainly don’t have machines giving us detailed explanations, at least not yet.

IBM would probably be better served aiming its commercials at the enterprises it sells to, rather than the general public, who may be impressed by a talking box having a conversation with a star. However, those of us who have at least some understanding of the capabilities of such tech, and those who buy it, don’t need such bells and whistles. We need much more practical applications. While chatting with Serena Williams about competitiveness may be entertaining, it isn’t really driving home the actual value proposition of this tech for business.

The trouble with using Watson as a catch-all phrase is that it reduces the authenticity of the core technology behind it. It’s not as though IBM is alone in trying to personify its AI though. We’ve seen the same thing from Salesforce with Einstein, Microsoft with Cortana and Adobe with Sensei. It seems that these large companies can’t deliver artificial intelligence without hiding it behind a brand.

The thing is this though, this is not a consumer device like the Amazon Echo or Google Home. It’s a set of technologies like deep learning, computer vision and natural language processing, but that’s hard to sell, so these companies try to put a brand on it like it’s a single entity.

Just this week, at the IBM Think Conference in Las Vegas, we saw a slew of announcements from IBM that took on the Watson brand. That included Watson Studio, Watson Knowledge Catalog, Watson Data Kits and Watson Assistant. While they were at it, they also announced they were beefing up their partnership Apple with — you guessed it — Watson and Apple Core ML. (Do you have anything without quite so much Watson in it?)

Marketers gonna market and there is little we can do, but when you overplay your brand, you may be doing your company more harm than good. IBM has saturated the Watson brand, and might not be reaching the intended audience as a result.

Mar
19
2018
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Apple, IBM add machine learning to partnership with Watson-Core ML coupling

Apple and IBM may seem like an odd couple, but the two companies have been working closely together for several years now. That has involved IBM sharing its enterprise expertise with Apple and Apple sharing its design sense with IBM. The companies have actually built hundreds of enterprise apps running on iOS devices. Today, they took that friendship a step further when they announced they were providing a way to combine IBM Watson machine learning with Apple Core ML to make the business apps running on Apple devices all the more intelligent.

The way it works is that a customer builds a machine learning model using Watson, taking advantage of data in an enterprise repository to train the model. For instance, a company may want to help field service techs point their iPhone camera at a machine and identify the make and model to order the correct parts. You could potentially train a model to recognize all the different machines using Watson’s image recognition capability.

The next step is to convert that model into Core ML and include it in your custom app. Apple introduced Core ML at the Worldwide Developers Conference last June as a way to make it easy for developers to move machine learning models from popular model building tools like TensorFlow, Caffe or IBM Watson to apps running on iOS devices.

After creating the model, you run it through the Core ML converter tools and insert it in your Apple app. The agreement with IBM makes it easier to do this using IBM Watson as the model building part of the equation. This allows the two partners to make the apps created under the partnership even smarter with machine learning.

“Apple developers need a way to quickly and easily build these apps and leverage the cloud where it’s delivered. [The partnership] lets developers take advantage of the Core ML integration,” Mahmoud Naghshineh, general manager for IBM Partnerships and Alliances explained.

To make it even easier, IBM also announced a cloud console to simplify the connection between the Watson model building process and inserting that model in the application running on the Apple device.

Over time, the app can share data back with Watson and improve the machine learning algorithm running on the edge device in a classic device-cloud partnership. “That’s the beauty of this combination. As you run the application, it’s real time and you don’t need to be connected to Watson, but as you classify different parts [on the device], that data gets collected and when you’re connected to Watson on a lower [bandwidth] interaction basis, you can feed it back to train your machine learning model and make it even better,” Naghshineh said.

The point of the partnership has always been to use data and analytics to build new business processes, by taking existing approaches and reengineering them for a touch screen.

“This adds a level of machine learning to that original goal moving it forward to take advantage of the latest tech. “We are taking this to the next level through machine learning. We are very much on that path and bringing improved accelerated capabilities and providing better insight to [give users] a much greater experience,” Naghshineh said.

Feb
27
2018
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IBM Watson CTO Rob High on bias and other challenges in machine learning

 For IBM Watson CTO Rob High, the biggest technological challenge in machine learning right now is figuring out how to train models with less data. “It’s a challenge, it’s a goal and there’s certainly reason to believe that it’s possible,” High told me during an interview at the annual Mobile World Congress in Barcelona. Read More

Jan
25
2018
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IBM brings Mendix’s low-code platform to its cloud

 IBM today announced a partnership with low-code development platform Mendix that will bring Mendix and native integration with many of IBM’s Watson IoT and AI services to the IBM Cloud. This deal is an evolution of a previous partnership that involved what was then called IBM Bluemix (now IBM Cloud). Read More

Jan
18
2018
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IBM’s year-over-year revenue didn’t decline in the last quarter

 Here’s a surprise: After 22 quarters of consecutive year-over-year revenue declines, IBM today reported that its revenue increased from Q4 2016 to Q4 2017. The company reported revenue of $22.5 billion for the last quarter, up from $21.77 billion a year ago. Read More

Jan
12
2018
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IBM may be prepping for massive changes at Global Technology Services group

 IBM has been a company adrift for the last several years with 22 straight quarters of declining revenue. Against that backdrop, The Register published an article yesterday suggesting there could be massive changes afoot for the company’s Global Technology Services group. Global Technology Services is the business consulting arm of IBM that deals with infrastructure support and… Read More

Jan
09
2018
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IBM led on patents in 2017, Facebook broke into top 50 for the first time

 Patents may sometimes get a bad rap for how they are abused (and misused) by some companies for commercial gain, but they also remain a marker of how a tech company is progressing with its R&D and pushing ahead on innovation. For one measure of that advance, today, IFI Claims, the patent analytics firm, published its 2017 list of companies with the most U.S. patents assigned for the year.… Read More

Dec
05
2017
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IBM’s new Power9 chip was built for AI and machine learning

 In a world that requires increasing amounts of compute power to handle the resource-intensive demands of workloads like artificial intelligence and machine learning, IBM enters the fray with its latest generation Power chip, the Power9. The company intends to sell the chips to third-party manufacturers and to cloud vendors including Google. Meanwhile, it’s releasing a new computer powered… Read More

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