Some No Code Platforms

A general exploration of current N-Code platforms.    Have been asked. 

12 No-Code Platforms for Some DIY Machine Learning   In NAnalyze

Only 25% of organizations are using artificial intelligence (AI) in their businesses today. Why? Custom AI-enabled solutions are expensive to build, as talented data scientists are a hot commodity today and don’t come cheap. Top performers can easily command over $250,000 in annual salary, which seriously makes us question the money we wasted invested in getting our MBAs. Not to mention, it can take months or even years to implement. CTOs are understandably suspicious of the latest buzzword du jour, so you need to show results fast.  ... ' 

Successful AR Solutions for the Enterprise

Took some long hard looks at AR for the Enterprise, but with little success.   Are we there yet?  Here a good piece, with some directions. 

How Augmented Reality Fits into AR  IoT

  Last year, we decided to add the German IoT company TeamViewer (TMV.F) to our Disruptive Tech Portfolio. It scratched all of the right itches – highly profitable with a 100% subscription model, crazy growth across different metrics, strong regional diversification, and foreign currency exposure. (It also doesn’t suffer from the ARK effect.) Its connectivity platform offers a suite of solutions that enable customers to remotely access, control, manage, monitor, and repair devices of any kind, from laptops and mobile phones to industrial machines and robots. We also like the fact that the company is integrating augmented reality into its IoT enterprise platform, adding a German AR applications startup to its portfolio in 2020. 

TeamViewer continued to build that part of the business in 2021, acquiring a U.S.-based AR startup, Upskill, this month. As investors, we want to understand the value that this new acquisition brings to the table.  ... ' 

Nanalyze on Brain Computer Interfaces (BCI)

Had forgotten about Nanalyze, worth a look: 

After I posted about it, they sent me this on Brain Computer interfaces:

Who we are We?     
We are a boutique media and research firm. Our research method involves sifting through large amounts of information in the public domain published by experts, then using our regular meetings and interviews with founders and industry participants to validate and boost our findings. ... 

This year we learned about a mind-blowing advance in brain-computer interface (BCI) technology for recording and interpreting neural signals. Founded by a wealthy and outsized personality, the West Coast startup has raised more than $100 million to advance the boundaries of neuroscience, augment human memory, and perhaps meld mind and machine in mind-bending ways. You know, modest goals like the rest of us. And, no, we’re not talking about painting lipstick on a pig in the way that Elon Musk is doing at Neuralink, a BCI startup that recently demonstrated its hardware hardwired into a poor little piggy. This story is about Kernel, a startup founded by Bryan Johnson that broke stealth mode (again) earlier this year with new mind-reading hardware powered by machine learning. It also unveiled its business model: Neuroscience as a Service (NaaS).

What is Brain-Computer Interface Technology?
Commercial BCI technology falls under the broader category of what’s become known as neurotech, which also includes applications like brain diagnostics and therapeutics, such as neuromodulation and electroceuticals. .... "   (More at the link above)

Indoor Positioning for Retail Innovation

We worked on this problem for our own innovation center tests.

A Smart Indoor Positioning System for Retail Automation

For the last few years we’ve been hearing about the retail apocalypse, though we would characterize it more as a retail extinction event. The difference being that until a couple of months ago, the demise of many brick-and-mortar businesses was a long, drawn out affair. No more. COVID-19 has caused a true retail apocalypse – goodbye, JCPenney, Pier One, J Crew, and company – by hastening the death of these ailing giants. There’s obviously a knock-on effect to tech companies shopping retail automation solutions. However, for one small Silicon Valley startup spun out of MIT, the novel coronavirus brought an unexpected opportunity for its thermal-based indoor positioning system.

You’re Being Followed
We’ve been covering the automation of retail for quite some time, from cashierless stores to robotic fulfillment centers in retailers like Walmart. The real money, of course, is in marketing. But it’s no longer necessary to blast messages and advertisements across a black hole and hope a few escape the gravitational pull of customer indifference. Today’s retail tech promises marketing precision by attempting to track and predict customer behavior in real-time both online and in the physical world. 

A company like Zenreach, for example, makes a pretty good case of ROI for its WiFi hotspot marketing software that tracks how well the store’s message is doing based on how many people walk through the door. Audio beacons are another way that stores can directly track customers by using sound to locate people through their smartphones. These technologies do start to leak into the creepy zone when you realize that the devices are communicating about you and your shopping behavior at a frequency you can’t detect. They also think you’ve put on a bit too much weight with all of the COVID-19 stress eating.

In fact, there are quite a few indoor positioning systems that scientists and startups have developed to track motion and trajectory. Not all of it is directed at marketing. WiFi motion sensors, for example, use WiFi signals for various smart home applications like security and even in-home elderly care, with algorithms trained to detect falls and too many trips to the cookie jar.

Briefly About Butlr  .... "

Using AI for Legal Contracts

Was just reminded of this effort: NAnalyze

Using Artificial Intelligence for Legal Contracts

" ... We made our first dive into how artificial intelligence is changing law practices a couple of years ago. At the time we noted that the $437 billion U.S. legal services market and the 1.3 million attorneys in this country aren’t going away just because of artificial intelligence and a few handy chatbots. Instead, AI will pick up the slack – initially – in tedious, repetitive jobs where it can be more efficient than humans. That brings us to legal contracts.

In an excellent analysis in the Harvard Business Review on how AI is changing contracts, writer Beverly Rich notes that the main challenge is the sheer number of contracts that law firms must track, many of which “lack uniformity” and are “difficult to organize, manage, and update.” That sounds like a job for natural language processing (NLP), a field of AI that deals with how machines understand (NLU) and generate language (NLG). The combined technologies help AI extract and understand unstructured and structured data. Part of the goal is for the machine to recognize context, which is a very hard thing for a machine to get because of the subtleties of our different languages.

Rich goes on to spell out the use cases and applications in using artificial intelligence for legal contracts:

“It can let companies review contracts more rapidly, organize and locate large amounts of contract data more easily, decrease the potential for contract disputes (and antagonistic contract negotiations), and increase the volume of contracts it is able to negotiate and execute… The use of AI contracting software has the potential to improve how all firms contract – and it will do so in three ways: by changing the tools firms use to contract, influencing the content of contracts, and affecting the processes by which firms contract.”