Non-Genetic Memory on Plants
Right… perhaps you don’t make sense out of memory and plants. Fact is, there’s more evidence that plants do find their way to communicate information.
As always this depends on how you define communication, or information. This new study by Yang, X., Sanchez, R., Kundariya, H. et al. shows that gene activation as response to initial environmental conditions can be transmitted to further generations of plants with no new stimuli nor genetic change. In some cases individual response to stress are transmitted down to next generations.
This is not hard to see as beneficial in evolutionary terms. What is hard in this case is to make peace with our egocentric view that plants, as the inferior life form we labeled them, would not be able to achieve such divine prerogative.
As consciousness researchers in general often realize, and studies such as we find in Peter Wohlleben amazing book ‘The Hidden Life of Trees’ we should more often rethink our ideas on plant complex existence.
Death of the office – by Catherine Nixey @ The Economist
As the corporate staff shifts the better part of its days from the office back home, many will ask ourselves about the time we normally spend in offices. As we move towards a new normal, what will be offices role?
“Created to ensure efficiency, offices immediately institutionalised idleness. A genteel arms race arose as managers tried to make their minions work, and the minions tried their damnedest to avoid it.”
Indeed, most of corporate labor has never experienced work outside office or even beyond office hours for a consistent period. Nor has the habit of spending weekdays daylight alongside children or family. Now we all have.
“The most transformatory aspect of offices was less the buildings themselves than the sheer amount of time we spent in them.”
At least for now, we have a critical perspective on how commuting, studying and working can be rethought. This essay offers some well written suggestive paths.
“The office has further-reaching patriarchal ploys up its sleeve. Chief among these is its response to children. Or rather lack of it. For most of history, workplaces ignored children entirely... ”
AI-powered SaaS: Science as a Service by Charles Yang
Charles Yang’s ML4Sci is a cool newsletter on AI and Machine Learning applications.
On #8 issue, his description of how AI powered Science as a Service brief us on how AI can be used to distribute science.
“AI-powered models are beating domain experts in protein folding predictions, speeding up scientific simulations, discovering novel antibiotics, and outperforming numerical weather models.”
All fine, but I want to bring attention to an underlying assumption in the SaaS: being a Service. Services measured by the results it provides such as more or less accurate its predictions. Perhaps more keen to machine learning terminology, one should read how accurate its classifications are.
Predictions are core to scientific development for a long time. Especially so in experimental science, the possibility of checking observations against predictions is an important part of what makes the theory falsifiable.
The novelty we see is that SaaS are not theories. Especially when we talk of Bayesian probability, big data, and deep learning. Often enough, small changes in the data bring very different results. Not to mention overfitting and other problematic predictive illusions.
So what? – asks the reader. So that instead of exchange of theories among scientists, science would evolve by sharing data silos. And instead of knowledge, we see scientific progress distancing human understanding of the nature of the universe.
If the apparent difference is irrelevant when we are trying to predict rainfall, how about economics or biology? Understanding the mechanics behind predictions in these fields may be as important as prediction accuracy.
In a broader picture, this may also lead to questions such as: if science becomes a service, wouldn’t we drive fast to a monopolistic scenario on science as we see in most data intensive AI business?
I will keep following both argument line in posts to come. For now let’s pay attention on those interesting developments.
And by all means, give ML4Sci a try.
Collaborative AI ?
May 2nd, 2019. Five hundred years ago today, Leonardo da Vinci died. Some say he was the last man to master frontier knowledge in all scientific fields.
The AI arms race appears destined to follow an unavoidable concentration pattern. Almost as the natural consequence of the fact that corporations leading the AI development embed the winner-takes-all economy we live in. It is hard to avoid top companies hoarding AI scientists. Not to mention the prize at the end of the rainbow – singularity – that would potentially be the ultimate step when the first in closes the gates for others. One AI to rule them all, so goes the omen.
For the last few hundred years, scientific progress has been a key drive for productivity and economic value creation. And this very science – built by Newton, Bayes, Godel, Turing, Bohr, to name a few – is the giant shoulder AI stands on. If we look back, despite the glorious contribution those geniuses individually made, the nature of the scientific progress in unquestionable a collaborative one.
Not that all science is to be replaced by AI, of course. For the time being, at least. Some science is, though. Additionally, a big part of scientific production now relies back on AI. It is hard to imagine theoretical physics, chemistry, or genetics nowadays without AI. This feedback loop would place scientific production into an analogous winner takes all path. Competition, not collaboration, would be the way to go.
Now: is it so? Let me dare to propose not:Continue reading
Fake memories in the making
Fake news, fake photos, fake audio, fake videos… all very bad compared to our own real objective reports, real image perception, real conversation reconstruction, real memory of witnessed events, right?
Wrong. All fake. No one really know the whole thing, but science indicates that all stories are subjective, our eyes don’t capture 3D images, we guess and forget and great deal of what we hear, and impression of memories are live reconstructs that can be altered as the whim of your mood. Which, by its turn depends on your gut bacteria health.
I am not saying all the new fake is welcome, nor that all innate fake is bad. But when we get great articles such as We’re underestimating the mind-warping potential of fake video
By Brian Resnick @ Vox we must remember that what is at stake is the privileged status of faking reality. Old ways, such as education and culture are in. New such as fake video, is out.Continue reading
Did you just see that?
The race towards capturing more frames per second has a new leader.
Publication at Nature Communications of paper describing compressed ultrafast spectral photography – CUSP. Researchers Peng Wang, Jinyang Liang, and Lihong V. Wang claim CUSP captures up to 70 trillion frames per second. We still can’t move in the forth dimension, but for now that’s the closest we get from standing time.
This is not out of the blue. For the record, this race have been going on for a while. Recent methods that are also in the trillion club are Lund University back in 2017 below, and STAMP camera developed in Japan a few years earlier.
micro-bots swarm
A flexible microsystem capable of controlled motion and actuation by wireless power transfer
Vineeth Kumar Bandari, Yang Nan, Daniil Karnaushenko, Yu Hong, Bingkun Sun, Friedrich Striggow, Dmitriy D. Karnaushenko, Christian Becker, Maryam Faghih, Mariana Medina-Sánchez, Feng Zhu & Oliver G. Schmidt