The balance of my articles on Diginomica 2019-2020other than AI: HPC/Supercomputers, Quantum, Cognitive, Complexity, Supply Chain, IoT, Edge Intelligence, Data, Telemedicine, healthcare Industry, For Good

1. Hired Brains Research LLC
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Neil Raden’s 2019-2020 Diginomica articles not about AI
The titles are live links
The technical realities of functional quantum computers - is Google’s ten-year
plan for Quantum Computing viable? ............................................................................ 2
The ups and downs of cognitive computing, from Watson to Amelia ......................... 2
Wrangling complex supply chains with Chaos Theory........................................... 3
When model drift becomes a deluge - the Coronavirus pandemic wreaks
havoc with data science and ML models.................................................................... 3
Can supercomputers play a role in the fight against COVID-19?............................. 3
Medical advancements need context - highs and lows from the Precision
Medicine World Conference ........................................................................................... 3
Telemedicine adoption amidst a pandemic - can we overcome the barriers?...... 3
Will telemedicine finally disrupt the health care industry?......................................... 3
After COVID-19, where does the US pharma and biotech industry stand?............ 4
Is digital transformation dependent on pervasive analytics? Not really.................. 4
COVID-19 pandemic models - are Machine Learning models useful?.................... 4
Solving data integration at scale - DataOps, knowledge graphs and
permissioned blockchains emerge................................................................................... 4
High Performance Computing matters - supercomputing and HPC as a
service in the real world .................................................................................................. 4
Apple and Johnson & Johnson team up for Heartline Study app - a
healthcare wearables breakthrough, or a questionable study? ........................... 5
Are you really disrupting, or are you running in place? Weighing both sides
of the disruption debate.................................................................................................. 5

2. Copyright 2020 Hired Brains Research LLC: All Rights Reserved 2
Federated machine learning is coming - here's the questions we should be
asking .................................................................................................................................... 5
Digital twins for personalized medicine - a critical assessment.......................... 5
Facial recognition revisited - can it save lives and actually protect privacy?.............. 5
Supercomputing and cancer research - is computational biology useful yet? ........... 6
Can we finally solve the demand and out-of-stock problem? NextOrbit says yes..... 6
DataOps challenge - the complicated art of making things simple .............................. 6
Big data didn't fall with MapR - Hadoop is fading, but data lakes are not................... 6
Data brokers and the implications of data sharing - the good, bad and ugly ............. 6
Some good advice on the challenges of securing the IoT............................................. 6
What can enterprise software learn from genomic research? ...................................... 6
Why you need to put Bayesian Nets in your tool bag..................................................... 7
Graph analysis - some off-the-wall use cases................................................................. 7
Ten rules for business models ........................................................................................... 7
I'm feeling sentimental about OLAP; you should too...................................................... 7
How to keep edge computing open for business - let the gorillas write the script.... 7
Data for Good - a question of relevancy........................................................................... 7
Sensory deprivation - 'garbage in, garbage out' revisited for the IoT era ................... 7
Modeling humans for personalized medicine - a prescription for trouble? ................. 8
Is Process Intelligence (Mining) a distinct discipline from analytics?........................... 8
The US insurance industry needs rebooting - here's why............................................. 8
digibyte: How not to do predictions for 2019 or any other time..................................... 8
The Data Warehouse is dead - long live the Data Warehouse..................................... 8
The technical realities of functional quantum computers - is Google’s
ten-year plan for Quantum Computing viable?
Google's quantum computing exploits have garnered plenty of attention in recent
months. But how might they apply this commercially? A contrasting technical view
comes by way of Itamar Sivan, CEO of Quantum Machines.
The ups and downs of cognitive computing, from Watson to Amelia
IBM Watson's health initiative underscored the limitations of applied cognitive computing. But
can a fresh wave of cognitive, conversational AI solutions like Amelia from IPsoft succeed with
a different type of offering?

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Wrangling complex supply chains with Chaos Theory
Complex supply chains are inherently chaotic, which means demand planners need
to understand Chaos Theory and the math behind it to unravel what's going on
When model drift becomes a deluge - the Coronavirus pandemic
wreaks havoc with data science and ML models
All predictive models are wrong - but some are very wrong. How did we wind up in
the
Can supercomputers play a role in the fight against COVID-19?
Yes, supercomputers are fast. But can high performance computers can provide
something unique in the fight against Coronavirus? Here's how supercomputers
have evolved, and a view of the COVID-19 work underway.
Medical advancements need context - highs and lows from the
Precision Medicine World Conference
The 2020 Precision Medicine Conference was loaded with practitioners solving real world
problems with tech. Here's my review of the best sessions, and a couple low points where the
tech hype overreached.
Telemedicine adoption amidst a pandemic - can we overcome the
barriers?
Far from being a cure-all, telemedicine brings a whole new set of pros and cons. The
barriers are not insignificant. However, a review of telemedicine adoption in the U.S.
and beyond provides a good incentive to press forward.
Will telemedicine finally disrupt the health care industry?

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In the U.S., regulatory pressures and per-state requirements have kept telemedicine
at a standstill. Emergency relaxation of telemedicine guidelines have changed the
picture for now - but will it lead to lasting change?
After COVID-19, where does the US pharma and biotech industry
stand?
The push for COVID-19 treatments has stoked the fires on big questions about the
US pharmaceutical industry, including drug pricing and conflicting data on drug
effectiveness. Here's my unvarnished take.
Is digital transformation dependent on pervasive analytics? Not really
Is the gap between data scientists and business analysts something the Alteryx
platform can bridge? Here's Alteryx CEO Dean Stoecker's view - and my critique.
COVID-19 pandemic models - are Machine Learning models useful?
Applying Machine Learning to Coronavirus data is tempting - but deeply
problematic. DataRobot shared lessons on working with smaller data sets, but the
predictive limitations of ML for assessing pandemics go much further.
Solving data integration at scale - DataOps, knowledge graphs and
permissioned blockchains emerge
Despite shiny new AI and data science tools, the problem of data integration at
scale hasn't gone away. But promising new approaches from vendors like StreamSets
and FlureeDB are worth a closer look.
High Performance Computing matters - supercomputing and HPC as a
service in the real world

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Advances in supercomputing aren't just for the geeky - High Performance Computing has real
world implications. Here's my take on some recent advancements, including HPC as a service,
and cloud deployments.
Apple and Johnson & Johnson team up for Heartline Study app - a
healthcare wearables breakthrough, or a questionable study?
Johnson & Johnson recently announced its Heartline Study app, which utilizes Apple Watches
and iPhones, with the expected fanfare. But is this really an advancement in wearables? And,
based on the official guidelines of clinical trials, does it qualify as a study?
Are you really disrupting, or are you running in place? Weighing both
sides of the disruption debate
The term "disruption" is widely used, along with "digital transformation." But are we using these
terms accurately? And what does real disruption look like? A recent debate brought these issues
to a head.
Federated machine learning is coming - here's the questions we should
be asking
With the introduction of Google's Tensor Flow federated, the hype around federated machine
learning is surging. But there are important questions about data privacy, performance and cost
that need answering.
Digital twins for personalized medicine - a critical assessment
Digital twins are amongst the most hyped technologies in recent years. It's time for a critical look
at the possibilities - and drawbacks - of digital twins for modern medicine.
Facial recognition revisited - can it save lives and actually protect
privacy?
Facial recognition technology has an ominous reputation - and for good reason. But are there
beneficial applications? Athena Security and D-ID believe the answer is yes. Here's my take on
our recent discussions

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Supercomputing and cancer research - is computational biology useful
yet?
What can you do with 1,000,000,000,000,000,000 Floating-point calculations per second
(EXAflops)? Simulate nuclear weapons? Yes. Cure cancer? Maybe...
Can we finally solve the demand and out-of-stock problem? NextOrbit
says yes
Retailers' attempts to solve out-of-stock and predict demand have a long history. But have we
finally turned a corner? A look at AI startup NextOrbit points to new possibilities.
DataOps challenge - the complicated art of making things simple
Variations on Dolly Parton - making things simple is pretty complicated.
Big data didn't fall with MapR - Hadoop is fading, but data lakes are not
The fall of MapR caused a rush to judgement about the future of Hadoop. To understand what
this means for data initiatives, the viability of Hadoop and data lakes must be separately
examined.
Data brokers and the implications of data sharing - the good, bad and
ugly
The term "data sharing" is expanding, but in a problematic way that raises flags for companies
and consumers alike. Neil Raden provides a deeper context for data sharing trends, dividing them
into the good, bad and ugly.
Some good advice on the challenges of securing the IoT
Surfacing the issues around securing the IoT.
What can enterprise software learn from genomic research?

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Advances in genomic research have changed our view of the human genome. Promising health
care advances are in the works, but we'll need massive computing power to see this through. Will
enterprise software as we know it change as a result?
Why you need to put Bayesian Nets in your tool bag
Casting a net over Bayesian Inference.
Graph analysis - some off-the-wall use cases
Graph technology is on the rise with some interesting applications.
Ten rules for business models
BI and business models take to the catwalk.
I'm feeling sentimental about OLAP; you should too
OLAP was big once; it still could be.
How to keep edge computing open for business - let the gorillas
write the script
How to keep edge computing open for business - let the gorillas write the script
Data for Good - a question of relevancy
Data for Good? A personal view from Neil Raden.
Sensory deprivation - 'garbage in, garbage out' revisited for the IoT
era
Sensor failure is a potential new threat to life in the IoT age.

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Modeling humans for personalized medicine - a prescription for
trouble?
Digital Twin technology for modeling individual people, or “personalized medicine,” is a
concept for simulating the whole.
Is Process Intelligence (Mining) a distinct discipline from analytics?
Why would you need a Process Intelligence package if you already have analytics skills or
even data science?
The US insurance industry needs rebooting - here's why
Few businesses stand to gain as much from digital transformation as insurance companies,
but few businesses encounter as many challenges when they try to implement it.
digibyte: How not to do predictions for 2019 or any other time
Predictions in tech media are two a penny but many are anything but predictions.
The Data Warehouse is dead - long live the Data Warehouse
Data warehouse technology is shifting to the cloud with much ballyhoo around new entrants.
But do they have the muscle to compete with the tried, tested and surviving incumbents?