“Never use a big word when a little
filthy one will do.” Johnny Carson
“Little minds have little worries, big
minds have no time for worries.” Ralph Waldo Emerson
“If you can build a business up big
enough, it's respectable.” Will Rogers
“If a financial institution is too big to
fail, it is too big to exist.” Bernie Sanders
Big data is a big deal. We humans generate so much data that our puny brains
are unable to process it. So we have created machines to do that for us.
There is a whole discipline called machine learning designed to train these
machines to process massive amounts of data in useful ways.
“Machine learning,” as Serdar Yegulalp notes in an InfoWorld article, “is a
complex discipline. But implementing machine learning models is far less
daunting and difficult than it used to be, thanks to machine learning
frameworks—such as Google’s TensorFlow—that ease the process of acquiring data,
training models, serving predictions, and refining future results.”
Yegulalp describes TensorFlow as open source software that “allows developers to create dataflow graphs—structures that
describe how data moves through a graph, or a series of processing nodes. Each
node in the graph represents a mathematical operation, and each connection or
edge between nodes is a multidimensional data array, or tensor.
“TensorFlow provides all of this for the programmer by way of the Python
language. Python is easy to learn and work with, and provides convenient ways
to express how high-level abstractions can be coupled together. Nodes and
tensors in TensorFlow are Python objects, and TensorFlow applications are
themselves Python applications.
“The actual math operations, however, are not performed in Python. The
libraries of transformations that are available through TensorFlow are written
as high-performance C++ binaries. Python just directs traffic between the
pieces, and provides high-level programming abstractions to hook them together.”
Read the full article at: https://www.infoworld.com/article/3278008/what-is-tensorflow-the-machine-learning-library-explained.html
TIP #1:
Consider how machine learning can impact your field of interest. Machine
learning also offers intriguing opportunities for people interested in
startups.
TIP #2:
For people who, like me, are not well versed in machine learning, consider
taking Google’s Machine
Learning Crash Course. It is free. Just go to …
https://developers.google.com/machine-learning/crash-course/ml-intro
///////
Starting Down the Startup Path: TOC – Table of Contents
If you enjoyed this post, you might like some of
the others in this series. Here is a convenient way to find them.
///////
Starting Down the Startup Path (Part 1 of a series)
How do you find emerging technology? One way is to focus on startups.
OK, fine, but how do you discover the startups that offer a technology of
interest to you? One way is to focus on venture capital
firms that focus on the areas of interest to you.
Read full post at:
https://desulf.blogspot.com/2019/12/starting-down-startup-path-part-1-of.html
Starting Down the Startup Path (Part 2 of a series)
Anyone involved in venture capital or its variants is interested in
identifying potential candidates for investment opportunity. Finding these
candidates is not easy. But a place to start on startups is to see what
companies other venture capital firms have identified.
Read full post at:
https://desulf.blogspot.com/2019/12/starting-down-startup-path-part-2-of.html
Starting Down the Startup Path (Part 3 of a series)
Panning for Google® gold: startups with promising new technologies
The previous post in this series featured the List of Top Oil and Gas Private
Equity Firms discovered as the result of a Google® search. The list focuses on
companies pursuing acquisition and development of existing resources. While the
list will be useful to many, this series of posts focuses on techniques you can
use to identify startups with promising new technologies.
So, on to the next step in the quest to find new technology on the cusp of
successful deployment.
Read full post at:
https://desulf.blogspot.com/2020/01/starting-down-startup-path-part-3-of.html
Starting Down the Startup Path (Part 4 of a series)
Nothing Ventured, Nothing Gained: Follow the Lead of the Oil Majors
How do you identify startups that fit your corporate goals? One way is to set
up and advertise a venture capital unit, which enables young companies to pitch
their technology to your corporation.
And that is just what several oil majors have done.
Studying their portfolios can provide a wealth of helpful information, whether
you are a venture capitalist, a startup, or simply interested in identifying
emerging technology.
Read full post at:
https://desulf.blogspot.com/2020/01/starting-down-startup-path-part-4-of.html
Starting Down the Startup Path (Part 5 of a series):
Searching Patents
Patents: Emerging Tech
Patents are a rich source of cutting-edge research. And much of the research
reported in patents never appears in peer reviewed journals. So, to identify
emerging technology in your field, consider searching the patent literature on
a regular basis.
TIP: Read Tips
for reading patents: a concise introduction for scientists for an
excellent overview on this topic.
Read full post at:
https://desulf.blogspot.com/2020/02/start-up-startdown-path-parti-5-of.html
Starting Down the Startup Path (Part 6 of a series):
Reviewing Patents
Searching for patents is iterative. You type in some keywords. Results reveal
more keywords. You type in those keywords. And repeat.
This can be really tedious, irksome even. Sometimes it is hard to figure out
whether a given patent is even relevant to your needs.
Fortunately, a number of experts have offered tips to make it easier to read a
patent quickly.
TIP: Google® how to read a
patent for more tips on efficient ways to review a patent
Read full post at:
https://desulf.blogspot.com/2020/03/starting-down-startup-path-part-6-of.html
Starting Down the Startup Path (Part 7 of a series):
Patents and Run On Sentences
Per USPO rules, the Claims in a patent must be stated in a single
sentence. In many cases, the “single sentence” can be, thanks to colons,
commas, semicolons, et al., several hundred words long.
But remember that, as difficult as it may be to wrap your head around any given
claim, it still is faster than reading the whole patent.
Read full post at:
https://desulf.blogspot.com/2020/03/starting-down-startup-path-part-7-of.html
Starting Down the Startup Path (Part 8 of a series):
Mining Patents for Keywords
Mining patents for useful information can be tedious. One thing you can
do is to look for keywords to use in Google® searches. For example, in a
previous post I listed a Breakthrough Technologies LLC patent with the
following claim …
Read full post at:
https://desulf.blogspot.com/2020/03/starting-down-startup-path-part-8-of.html
Starting Down the Startup Path (Part 9 of a series):
PTQ Catalysis 2020
PTQ Catalysis 2020 is ready to view at www.eptq.com. As always, it is
rich in useful information. In the context of our Startdown the Startup Path series
of posts, one article in particular caught my eye …
Pilot plant studies of hydrotreating catalysts
Read full post at:
https://desulf.blogspot.com/2020/03/starting-down-startup-path-part-9-of.html
Starting Down the Startup Path (Part 10 of a series): The
Bigness of Machine Learning
Big data is a big deal. We humans generate so much data that our puny
brains are unable to process it. So we have created machines to do that for us.
There is a whole discipline called machine learning designed to train these
machines to process massive amounts of data in useful ways.
“Machine learning,” as Serdar Yegulalp notes in an InfoWorld article, “is a
complex discipline. But implementing machine learning models is far less
daunting and difficult than it used to be, thanks to machine learning
frameworks—such as Google’s TensorFlow—that ease the process of
acquiring data, training models, serving predictions, and refining future
results.”
Read full post at:
https://desulf.blogspot.com/2020/03/starting-down-startup-path-part-10-of.html
Starting Down the Startup Path (Part 11 of a series):
Thread the Needle
In a horse race, the goal is to bet on the winning horse. Common sense tells us
that if we knew for a certainty which horse would win the race, racing them
would be pointless. The same logic applies to new technologies, and the
companies that create them.
That’s why it can be useful to look at companies that have been examined by
investment funds like the Columbia Seligman
Communications and Information Fund.
Read full post at:
https://desulf.blogspot.com/2020/04/starting-down-startup-path-part-11-of.html
Starting Down the Startup Path (Part 12 of a series):
Patent Prior Art Search
Prior Art Search: Everything you need to know
If you’re looking to understand everything about prior art search,
you’ve landed on the right page. By the time you finish reading this guide,
you’ll likely have built a solid understanding of what can be included in the
prior art, how you can use this knowledge to conduct a patent search all by
yourself and avoid spending valuable resources on the non-patentable subject
matter.
Read full post at:
https://desulf.blogspot.com/2020/04/starting-down-startup-path-part-12-of.html
Starting Down the Startup Path (Part 13 of a series)
Dibenzothiophene Patents 2020
What’s the quickest way to determine if a patent is of interest to you?
Depends on your purpose. This tip sheet may help you decide which section of a
patent to focus on.
Read full post at:
https://desulf.blogspot.com/2020/05/starting-down-startup-path-part-13-of.html
Starting Down the Startup Path (Part 14 of a
series)-Google Patents Find Prior Art Link
Patent research is important in any area of research you are engaged in
... especially if you are a startup, or are considering investing in a startup.
Prior art is an important concept in patent research.
In this regard, Google® Patents Prior Art Link is useful. When you
find a patent of interest, in the upper right of the screen you will find a
link labeled Prior Art.
Read full post at:
http://desulf.blogspot.com/2020/05/starting-down-startup-path-part-14-of.html
///////
Google® Better!
Jean
Steinhardt served as Librarian, Aramco Services, Engineering Division, for 13
years. He now heads Jean Steinhardt Consulting LLC, producing the same high
quality research that he performed for Aramco.
Follow Jean’s blog at: http://desulf.blogspot.com/
for continuing tips on effective online research
Email Jean at research@jeansteinhardtconsulting.com with questions on
research, training, or anything else
Visit Jean’s Web site at http://www.jeansteinhardtconsulting.com/
to see examples of the services we can provide
No comments:
Post a Comment