Digital Manufacturing: At My Ventures


[Work in Progress …]

Youtube Playlist (Compiled By Me):

Digital Manufacturing: What happens when you employ Digital Technologies to Manufacturing? Discover for yourself! #AtMyVentures




Manufacturing Cloud

Link: Physical Digital Integration: Manufacturing Cloud & Car 2.0  []



Additive Manufacturing & 3D Printing

Internet of Things (IoT)

Sensors & Big Data

Industrial Internet

Enterprise Physical Computing

Science & Engineering News: Google, Surgical Robots, Airports & More …





Smart Home


Britain: Materials


Digital Car

“The Freightliner SuperTruck improves fuel economy by 115 percent and cools the cargo compartment with solar power”


Construction & Architecture: Airport



“Connecting 29-year-old technology to the modern internet is a crazy, complicated labor of love!”


Engineering & Sciences: Biotech & More


Engineering & Sciences: Biotech & More



Biotech Ventures

“The wider change is that biology is getting cheaper and easier to do.”

Frontiers Of Engineering & Technology

Frontiers Of Engineering & Technology : Research & Engineering (R&E)

Energy & Power

Energy & Power: Materials for Solar

Energy & Power: Decentralized Power Grid

Energy & Power: Smart Solar, Smart Wind

Artificial Intelligence

Artificial Intelligence : Machine Learning


Robotics: Augmented Robotics; Service Robotics 

Robotics: Drone / Unmanned Aerial Vehicle (UAV)

Robotics: Agile Robotics

Medicine & BioEngineering

Medicine & BioEngineering: Computational & Systems Biology

Medicine & BioEngineering: Genomics, Molecular Biology & Molecular Medicine


Computational Neuroscience & NeuroEngineering

Computational Neuroscience

America In Realization [02.25.15]

Business & Economics : The Economics of “Automation” 


“Experts rethink belief that tech always lifts employment as machines take on skills once thought uniquely human”

প্রিন্সেস শামিতা তাহসিনকে লেখা চিঠি – ২৪


Princess, Catholic Church র Father রা লক্ষ্য রেখেছে আমি যাতে বড় লক্ষ্য নিয়ে কাজ করি। কারণ, “ও যা চায় করতে পারবে, যা হতে চায় হতে পারবে – শুধু লক্ষ্যটা বড় রাখতে হবে।”


Father’রা ভাবল, আমাদের Christ তাহলে CS র লোক!

[Think this way: Someone comes to you and says, Jesus Christ is a CS Major!

Church Fathers look at me from that perspective.]

ওরা জেনে নিল CS র সবচেয়ে Advanced, Significant কাজ কোন sub-field-এ হচ্ছে।

সবাই suggest করলো – Big Data.

Father রা চাইল, আমি Big Data নিয়ে কাজ করি।

আমি তখন বাংলাদেশে। ওরা suggest করলো Big Data দেখতে – CS আর Applied Mathematics দুটোর উপর emphasize করলে সবচেয়ে ভালো হবে।

আমি CS এর যেহেতু – ওরা দেখতে চাইল, আমি Google, Facebook, Apple আর Amazon র মধ্যে কোনটাকে Prefer করি। ওটার-ই Dominate করার কথা।

দেখা গেল Google.

2013. Why is Google Building A Robot Army?

এবার Father’রা ভাবল, Christ কে Christ এর মতই হতে হবে! শুধু CS নিয়ে থাকলে তো চলবে না। ওর Medicine, Life Sciences এর দিকেও যাওয়া উচিত।

Google কে suggest করলো, Life Science Research, Anti-aging এ invest করতে।

Google তখন Anti-aging Research এ invest করে। Established হয় Calico [1]

US Department of Defense এর লোকজন ভাবল, Tahsin কে দিয়ে United States’র জন্য Military Robot বানাতে হবে।

Defense Research নিয়ে Plan জানিয়েছিলাম – Military’র কেউ injured হওয়ার চাইতে Military তে Robotics এর আরও বেশি use হওয়া উচিত – Fighter Aircraft-র বদলে Drone ব্যবহার করার মত।

Google কে suggest করা হল – Boston Dynamics (DARPA funded) [2] সহ আরও কিছু Robotics Firms কিনতে।

2013 এ তা-ই হল। Google ৮টা Robotics Firm কিনল [3]

এগুলো হল ঘটনার পেছনের ঘটনা। ( Why is Google Building A Robot Army? [Popular Science] )


“The Search giant is launching a venture to extend the human life span”

Sept. 30, 2013

Sept. 30, 2013

Articles By Me

Latest From Science & Engineering, Medicine & Innovation [02.15.15]

Apple : Apple Car – “The iCar” ?  #21stCenturyRenaissance  #DigitalCar

“IPhone Maker Has 100s Working on Design of a Minivan Like Vehicle”


Apple : Apple Search Engine   #21stCenturyRenaissance

How to create “The Next Silicon Valley” [A vibrant Tech & Entrepreneurial Hub]  #21stCenturyRenaissance

Physical Digital Retail   #PhysicalDigitalRetail  #21stCenturyRenaissance


A brief overview of the nature of Physical Digital Retail  #21stCenturyRenaissance

Retail has become a blur – with Physical Stores and Online Retail (together with Mobile) – each approaching the other to create something new – Physical Digital Retail.

Target, Macy‘s and Walmart, the Physical Stores, are focusing on

  • Online Retail and
  • In-store Mobile Tracking & Commerce

while Amazon and Google, the online giants, are investing in

  • “Same-day delivery Services” (the “instant gratification” factor – that only Physical Stores could offer in the past).


“In-store” Intelligent interfaces that interact with customers are beginning to make their appearances in Physical Stores.

Big Data and Analytical Tools will get popular among Physical Retailers for tasks such as

  • Sales pattern investigation
  • Supply chain management (SCM)
  • Product placement in Stores (utilizing methods such as Market basket Analysis).


Physical Digital Retail” is big!


Youtube Playlist (Compiled By Me):

Physical Digital Retail : What does the future of Retail look like?

Notes On Research & Engineering (R&E) : Electrical, Mechanical, Chemical & Bio Engineering

Areas of Expertise:

#Electrical Engineering   #Mechanical Engineering

#Chemical Engineering  #BioEngineering

Academia To Industry – Technology & Innovation Transfer 

In Academia, lots of Science, Tools & Techniques are in incubation phase, not ready to be incorporated into industrial products.

I shall turn Science, Tools & Techniques into Engineering Innovations.

Engineering -> Product & Service Innovation At My Ventures

Engineer’s Approach:

How do I use “a specific Technology” (For example, Internet of Things) in a specific product?

[Example: Let’s connect our Thermostat or Micro-wave Oven to the Internet of Things (IoT).]

My Approach:

  • Study a “Domain” (For example: Home, Manufacturing, Sports, Education, Healthcare, etc.) and
  • Find out how Engineering could be applied to this specific “Domain”. Engineer Products & Services using “All Possible Technologies”.

It’s possible, because

  • I am not limited by a specific field of Expertise [say, “Software Engineering” or “Internet of Things (IoT)”]
  • But I can employ all of Human Knowledge and any Domain of Expertise ( to meet the challenges of a specific domain or problem in hand; whereas Engineers are limited by specific fields of Expertise.

Electrical Engineering

Application Areas:

1. Physical Basis of Information

2. Power

  • EE : 1. Physical basis of Information

VLSI & Computer Systems

Manipulation of Information with Transistors, etc.

Communications Technology

Exchange of Information.

Entertainment Technology

[Example: Image -> Electronic Representation as Information).

Transducers and Sensors

Turning Physical Quantities into Electrically Represented Information

Signals & Systems

Signal is basically Information

Control Systems

Control with the use of Electrical / Electronic Signals

  • EE : 2. Power

Scientific Basis of Electrical Engineering:

  • Electricity. Magnetism. Electrical Circuit. Electromagnetism. Optics & Photonics. Solid State & Condensed Matter Physics.

Mechanical Engineering

Application Areas:

  • Mechanics & Machines

Scientific Basis of Mechanical Engineering:

  • Mechanics; Solid Mechanics; Fluid Mechanics; Thermodynamics; Electro-magnetic Induction.

Chemical Engineering

  • Phenomena that have “Chemical Basis”.


Complex Fluids & Transport  <- Chemical Basis, Chemical Composition.

Food Processing.

Petrochemical Industry.


  • Sensing Life


Signal Processing.

Genome Sequencing.

  • Modeling Life

Computational & Systems Biology. Bioinformatics.

  • Manipulating Life

Drug Design, Drug Delivery & Biomaterials.

Regenerative Medicine & Stem Cell Technology. Tissue Engineering.

Genetic Engineering. DNA Editing.


Endoscopic Surgical Tools. Surgical Robots (Example: Da Vinci Robot).

Prosthetics. Artificial Retina.

Articles By Me:

AeroSpace Engineering -> Commercial Aircraft

AeroSpace Engineering -> Commercial Aircraft

Latest From Science & Engineering, Medicine & Innovation [01.19.15]


Internet of Things (IoT)

A Look at Internet of Things (IoT) Industry as it stands Today

Analysts predictions (Internet of Things Global Market): 1.9 trillion from Gartner IT 2.44% , 7.1 trillion from IDC, 19 trillion from Cisco CSCO 0.99% .

Smart home: Nest (bought by Google), SmartThings (bought by Samsung)

Wearables: Smartwatches, fitness trackers, and pet-tracking gadgets

Industrial Internet: GE  …. Companies (that GE sells Industrial Equipment to)  use … data from sensors, like improving fuel efficiency and making trains run faster.

Chipmakers: Intel, Qualcomm, ARM Holdings.

Wireless-device makers, Networking Equipment Makers: Sierra Wireless, Cisco, Aruba, Ruckus Wireless, Netgear.

Big Data: Splunk, Hortonworks.

Smart Cars:    #SmartCar

  • Electric / Hybrid / Fuel-cell Cars.
  • Autonomous / Semi-autonomous Cars.
  • Sensors – Data:
    • More Fuel Efficient.
    • Collision Detection.
    • Automation.
  • Connected (IoT).
  • New User Interface (UI) – Not Traditional “Steering wheels” and “Gears” and “Speed Readers”, rather New “Controls”.
  • Manufacturing: Digital Manufacturing; New Materials; 3D Printed (parts) and then assembled.

Artificial Intelligence: Platforms & Apps – At My Ventures

Youtube Playlist (Compiled by me): Artificial Intelligence “Platform”

Artificial Intelligence: “Platforms” & “Apps”  


Artificial Intelligence & Robotics “Platform”  #AtMyVentures

3rd Party Applications, Services & Robots built on top of the Platform

The “Intelligence” behind Smart Connected Products – “Platform”

[Current Generation Instance: IBM Watson]

Knowledge Based Robotics, Expert Robotics 

[Articles By Me: No. 11]

Augmented Robotics 

[Articles By Me: No. 11]

Next Generation Web Search Engine  #AtMyVentures

A Search Engine based on Real World “Entity” Recognition in Webpages and Information Extraction (IE)

Rather than just Word indexing and Hyperlink Analysis (Current Generation Web Search Engine – introduced in 1998 by Sergey Brin and Larry Page through the Google Search Engine.)

We have had the same Search Engine technology for the past 17 years, with little incremental improvements.

Incremental Improvements included:

1. Refining Search Results based on User Clicks, etc (using Machine Learning Models. Changing “Parameter” values in Equations and testing to find out if users like the newer version more).

2. Parallel & Distributed Processing (to handle the ever increasing size of the Web and the number of Documents it contains)

3. Caching Search Results (for faster responses)

4. Adding “External” Semantic Data on the Search Result page, and in “Domain Specific” Search Engines (e.g., Books, Shopping, etc.).

Instances: Google bought Freebase and integrated the “Knowledge Graph”. Microsoft bought Powerset – the Wikipedia Search Engine.

Big Data 2.0 => New Kinds Of Sciences  #AtMyVentures

[Articles By Me: No. 3]

Link: “New Kinds of” Social Sciences  []

Recommendation Systems

Provides Recommendations utilizing Models based on “New Kinds Of Sciences”

Service Agents  #ServiceAgent  #AtMyVentures 

Artificial Agents that can perform “Service” Industry Jobs

Example “Service Agents”:

“Airline Ticket Reservation Agent” that assists you in buying your Airline Tickets, taking all your personal requirements & constraints (budget constraints, time constraints, etc.) into consideration.

Agents that can replace “Call Center” Workers

Personal Agent  #AtMyVentures

That act as an “interface” to the World around you.

State of the Art “Personal Agent”:

Google Now

Microsoft Cortana

Apple Siri

Agents Across Different Verticals

Medical Diagnostic Agent

Personal Finance Management & Recommendation Agent

Articles By Me

  1. What is Machine Learning? [TahsinVersion2]
  2. Overview of (Artificially) Intelligent Agents
  3. Notes On Intelligence & Data Computing (1) [TahsinVersion2]
  4. Personal Notes On Distributed Data Computing [Unofficial]
  5. Subfields Of Sciences As Inspiration For Machine Learning Algorithms/Paradigms
  6. Personal Notes On Artificial Intelligence [Unofficial]
  7. Personal Notes On Intelligence & Data – 1 [Unofficial]
  8. Machine Learning Algorithms: Brief Introduction
  9. Application Of Data Analytics, Mining, Machine Learning & Network Science To Election Campaign Strategy
  10. Distributed Data Processing Frameworks
  11. Notes On Robotics [Knowledge Based Robotics; Augmented Robotics; Transportation & Vehicle Robotics] (TahsinVersion2)
  12. Short Review of “How to create a Mind” by Ray Kurzweil and “On Intelligence” by Jeff Hawkins [TahsinVersion2]
  13. Latest From Science, Technology, Medicine & Innovation [12.16.14] [TahsinVersion2]
  14. Latest From Science, Engineering, Medicine & Innovation [11.12.14]
  15. Quora Question: Which Subfields Of The Sciences Have Been Most Fruitful In Inspiring New Machine Learning Algorithms/Paradigms? [TahsinVersion2]
  16. Open Letter To Princess Shamita Tahsin – 10 [TahsinVersion2] (Artificial Intelligence … MetaCognition)