I was at the magazine rack at a Chapters the other day in hopes of discovering a new publication to add to my readings, low and behold I found two: MIT Technology Review, and the Stanford Social Innovation Review. If a pattern in my magazine choices has become evident, I guess I’ll admit to being a sucker to the weight of big university names. In any case I skimmed a few articles in each and found a breadth of interesting topics and so I picked the two up. Below are some of the highlights of my readings thus far.
I’ve started off on the Technology Review. Maybe I’ve not been indulging myself in the latest of tech related topics as I once use to and so my brain lit up at all the exciting technological advancements that I have seemingly gone unaware of. The feeling also reminded me of how easy I can find myself following an unending yet fascinating rabbit hole of scientific news and breakthroughs. Without any meaningful comprehension of the underlying science I walk away with the instant serotonin hit from glimpsing at cool things but ultimately unsatisfied with my lack of any lasting knowledge. Hence, if I were to direct the euphoria to a constructive gain like a little writing I may find myself feeling less guilty for getting sucked in.
The topic of Immune Engineering was the focus of one of their lengthier pieces in the review and a subject that I have mostly gone unaware of. I’m inclined to do a little more reading up before I try to tackle the topic in any sort of depth, but I understand it to be the replication and enhancement of the bodies natural auto-immune response to extremely difficult diseases including cancers and HIV. The outcome of the field is to genetically engineer immune cells that are capable of eliminating pathological cells with the same efficacy as they might the common cold.
The breakthroughs of the this type of engineering in the way of Immune Therapy, have been astounding to say the least and some high profile success stories have prompted a surge of research dollars both private and public to advance the cause. An aspect that inspires thoughts of contributing to the cause is when the article highlighted the works of a lab a part of the Mount Sinai hospital and medical school which employs a dozen or so programmers to develop software that interprets DNA sequences in patients cancer cells. The insights revealed by the sequence interpretations will be the focus of a clinical trial that will attempt at training a type of immune cell in the body known as T-Cells to attack cells with the genetic abnormalities of cancer cells more readily and efficiently.
To continue down the vein of genetic engineering, is the subject of precise gene editing in plants. A technique known as CRISPR (how cute) developed by Caribou Biosciences, allows the precise manipulation of genetic code to trigger biological enhancements we might associate with GMO foods (an unfortunate misnomer by the way): drought resistance, fungal resistance.
Why this isn’t considered GMO plants in the regulatory sense is that the edited plants in as early as the second generation do not contain the foreign DNA used to create the first generation. I’m really not sure what that means, again maybe something I might be inclined on reading up more on for a future post. All that aside, if regulations can be considered more lax on this technique, it may reduce the high barrier to entry as a GEO (genetically engineered organisms) seed producer. Potentially disrupting the large monopoly on seeds consisting of the likes of Monsanto, Dupont and Syngenta, which isn’t to say there has not been interest in the technique by the aforementioned companies.
Shared Robot Learning
This next idea struck me as remarkably simple and yet so remarkable. The idea of a shared database of robot how-to’s which would empower robots of a more tactile/motor functional purpose to collectively upload their experiences of how to accomplish particular tasks such as manipulating various objects. The combined efforts of an increasing usage of robots such as Baxter could accelerate the diversity and complexity of tasks a robot could accomplish right out of the box.
Apparently a standard framework for programming robots known as ROS is already shared amongst most research robots which make such an effort possible today. A project called RoboBrain demonstrated the cross-learning capabilities of different robots by downloading the instructions to pick-up a couple simple household objects from a PR2 robot into a Baxter which is physically different to perform the same task in a different environment.
From my point of view such a variety of combined experiences may one day even empower such robots to employ deeper problem solving skills by applying nuanced combinations of similar tasks when faced with seemingly unencountered obstacles. Experiences which naturally would be uploaded to the collective robot hive mind (I say with a touch of good humour).