Requirement

Master’s or PhD degree in Information Science, Information Studies, Information Systems, or Library and Information Sciences

Duration: part-time, minimum 7 hours per week

Work Hours: Flexible (intern can work at any time, including nighttime or on weekend)

Location: Remote (Intern can live anywhere in the world.)

Primary Work Premise: Home

Compensation: $15 (US Dollar) per hour

Consideration for full-time employment: Yes

Training Provided: Yes.

Travel Required: No

Submission Requirements:

Please upload Resume (in English)

Interview format: Video interview via Zoom or Microsoft Teams will be arranged upon selection notification

1. Background: IPwe is Erich Spangenberg’s latest IP focused venture – lots of information on him on Google about his patent businesses. IPwe is using exponential technology to create the patent asset class— an IP marketplace that does not exist today. We work with the largest companies and universities in the world and also many others (mostly small businesses) and provide AI driven analytics and facilitate IP related transactions

2. Need: We spend a fortune on AI development (largely predictive analytics), and a key thing we need is data/information that tends to reside in obscure places. We have a full library of the world’s patents (for example). Now we are on a mission that includes:

a. Building a relevant prior art library (finding technical libraries) (retrieving non-patent literature (such as scientific journals, articles, university publications, technology articles, etc.)

i. For example IBM has a “red book” library that sits behind a firewall – it has tons of research in it on a myriad of products/ideas

ii. MIT and Cisco tried to do this but the project just died – we can pull it off

b. Licensing – finding information on existing patent licenses (similar to other financial information existing at SEC)

c. Identifying more obscure/hidden data sources to answer fundamental questions relating to innovation

i. Simple: Who are the leaders in a particular technology area

ii. More Complex: What are the licensing rates applicable to 5G technology

iii. Complex: What is the next communications technology that may replace 5G

d. Signals – finding things like what makes innovation work and how to identify it earlier; a database of utility bills (if your utility bills are going up, chances are your company is growing…if they are declining, that is another issue); etc.

e. Identify other “relevant” data sources

3. We then take these data sources and run them through our AI systems and give people answers/actionable intelligence

We already built a database since 2007 of the world’s patents. In 2007, our team acquired a spinout from the University of Minnesota, and built this patent database. 25 million dollars was invested into this tool, now called IPwe Analytics.

We have 80% of the world’s patents. We have over 3 million non-patent literature (NPL) documents, such as technical and scientific journals.

Currently, IPwe Analytics focuses in on “prior art” analysis. In particular IPwe Analytics relies on searching over 59 million patent and patent application records dating as far back as the early 1900’s and over two million articles and journals we have legally obtained and indexed and regular downloads from the Internet, which we call our “IPwe Analytics Prior Art Library.” The IPwe Analytics Prior Art Library is constantly being updated and we are working with a number of third parties to establish an even larger library of key prior art references. In the near future, we plan to make the IPwe Analytics Prior Art Library available to any third party that commits to contribute and share in the goal of creating a relevant prior art library accessible by all.

No patent knowledge is necessary. You don’t need to worry about how the patent analytics tool works. The tool has the patents in the repository.