With Amazon mobile wallet, consumers will be able to move seamlessly through the online shopping funnel, thanks to automated know-your-customer (KYC) and authentication for merchants. As important, these wallets will attract customers who have been forced to abandon cash after the Indian government’s demonetization program during the last six months. Focused on this void in the payments space, Amazon should be able to leverage Amazon Pay, gift cards, and digital wallets to gain significant market share in India.

Blockchains Could Play An Important Role in Machine Learning

This week we took a break from discussing cryptoasset market action and focused instead on an interesting article written by Fred Ehrsam, co-founder of Coinbase, titled: “Blockchains are a data buffet for AIs.” Because of their transparent and their immutable recording of activity over time, blockchains could provide the data to train machine learning algorithms. Fred argues that “AIs trained on open data are more likely to be neutral and trustworthy instead of biased by the interests of the corporation who created and trained them.”

Data aggregators like Facebook, Amazon, Netflix, Google and others could find their massive data sets - and business models - increasingly challenged by these open data structures. Open sourced hardware and software have paved the way for open sourced data.

Meanwhile, Ethereum crossed the $6 billion market cap this week, while bitcoin pushed through $20 billion and the cryptoasset space as a whole is approaching $35 billion. We are witnessing the evolution of a new asset class.

REMINDER:

Along with William Mougayar, CoinDesk, Coin Center, and others, ARK is helping to organize the Token Summit. This is a first-ever event exploring the economics, regulation and best practices around the issuance and operations of new cryptoassets. You can sign up for this two-day event occurring on May 24 and 25 in NYC here.

Autonomous Car Services Could Be Ready For Prime Time

Google’s Waymo is preparing to open its self-driving cars in Phoenix to public transportation, its first step toward commercializing its autonomous car service. While Google probably has the best autonomous car technology in the market, Tesla has been more aggressive in its commercialization efforts. Tesla is using its customer fleet to test and improve its autonomous driving systems through its Autopilot program.

Google’s Phoenix pilot should give it more real world data to train its autonomous cars. Participants must apply to join the pilot, and if accepted, will gain access to the Waymo fleet in Phoenix “every day, at any time,” much like a subscription ridesharing service.

Waymo also is adding an additional 500 Fiat Pacifica Hybrid minivans to its self-driving car fleet, bringing the total fleet size to around 650 cars in the US, including 20 Lexus SUVs, 30 Google pod cars, and 600 Fiat minivans. Google will have the largest test fleet of autonomous cars in the US, with GM’s Cruise Automation in second place at around 350 cars. With a larger fleet, Google will have a bigger data library and more cases to train its cars.

Fiat’s earnings call this week confirmed that it is relying on Google for autonomous technology, although it is open to other partnerships and may strike a deal with Baidu in China. Honda was also rumored to be in talks with Googe’s Waymo for an autonomous partnership. ARK anticipates that more automakers will partner with Google as they realize the difficulty of building their own platform.

What Is Going On with Illumina and Index Swapping?

Led by Illumina, next generation sequencing technology has improved dramatically recently, albeit with some growing pains. Recently, the life science’s community has highlighted an error known as index-hopping or -swapping during RNA sequencing: “reads from sample A in an A:B mix will contain a small percentage of reads from sample B and vice versa,” according to genomics blog Enseqlopedia.com. While not a problem for most experiments, index-swapping could be problematic for a few, particularly those involving tiny amounts of RNA.

The issue of cross-contamination, discussed somewhat esoterically after Illumina introduced its ExAmp technology, took on more importance after a researcher from Stanford, Rahul Sinha, published his findings about the problem on BioRxiv in April 2017. According to a white paper subsequently published by Illumina in April, “exclusion amplification (ExAmp) chemistry and pattern flow cell technology [is] a significant advance in NGS technology that resulted in increased data output, reduced cost, and faster run times,” and helped enable the $1000 genome. At the same time, Illumina also noted that the technology does result occasionally in higher levels of index swapping, in the 0.1 – 2% range.

While potentially an issue for a small percentage of researchers, Illumina is not minimizing the importance of index-swapping and addressed it during its first quarter earnings call, confirming that it is working with customers to understand the situation and share best practices. Furthermore, in a white paper, Illumina highlighted that it is working on a permanent solution for index-swapping and does not expect it to impede the progress of NovaSeq, its next generation sequencer. According to ARK’s research, NovaSeq is on course to sequence a whole human genome for $100 around the turn of the decade, adding its access to the global population.

[1] RedSeer Consulting data shows that Prime subscribers grew rapidly to reach 6 million in six months since its launch.

Originally Published at: Developments in Instagram, Amazon, Blockchain, Autonomous Cars, and Illumina