D&NA group Tokyo

Droplets & Nucleic Acids group in LIMMS/CNRS-UTokyo,

DNA computing 🧬👉💻
DNA storage 🧬👉🗄️
DNA materials 🧬👉🍮
DNA diagnosis 🧬👉🩺

[CNRS in North-East Asia @CNRSinJapan]

The 🇫🇷Minister of Higher Education and Research @sup_recherche just visited the @LimmsTokyo joint Int’l Research Lab between @CNRS @INSIS_CNRS and @UTokyo_News_en @UTokyo_IIS on Komaba Campus, true success story of the 🇫🇷🇯🇵research collaboration.
Thank you Ms. Minister !

[Yutaka Hori @hori_yutaka]

Our new microfluidic device for "chemical function generator" is published! The device enables to generate dynamic concentration waveforms for chemical stimulations based on the electronic-hydraulic analogy of an R-2R ladder D/A converter circuit.
https://t.co/A6jmfamEgQ

[Seth Bannon @sethbannon]

https://t.co/7TYKrcdFI5

[Ethan Mollick @emollick]

Some lessons of the insane past 4 days of generative AI, as someone who had access to Bing during and after the "Sydney" era. (Trying this as a long tweet rather than a thread...)

1) Bing AI was two things: a chatbot and an evolution of ChatGPT into a web-connected, supercharged form. There is no reason these two things had to be connected, but they were.

2) The new Bing AI version of search and retrieval (without the chatbot) is much more powerful than ChatGPT. It has some of the same issues (like hallucination and terrible math) but less so, and is capable of some really extraordinary tasks. When I put it to the test, it can do things like read multiple research papers and identify gaps; improve its own writing by asking it to look at online examples of good writing; and do complex analyses integrating diverse information. The work was really, really impressive.

3) The Bing Chatbot was often unsettling. I say that as someone who knows that there is no actual personality or entity behind a LLM model. But, even knowing that it was basically auto-completing a dialog based on my prompts, it felt like you were dealing with a real person. I never attempted to "jailbreak" the chatbot or make it act in any particular way, but I still got answers that felt extremely personal, and interactions that made the bot feel intentional.

4) The lesson of the Chatbot was that we can very easily be fooled by an AI into thinking it is sentient. It isn't just Turing Test passing, it is eerily convincing even if you know it is a bot, and even at this very early stage of evolution. Even if Bing isn't doing this anymore, there is no doubt other AI bots will come along, and may already be deployed (I assume governments have LLMs at the level of Bing, but with less guardrails). We should be considering about what that means.

5) The lesson of the Bing AI version of ChatGPT is that many of the things we thought AI would be bad at for awhile (complex integration of data sources, "learning" and improving by being told to look online for examples, seemingly creative suggestions based on research, etc.) are already possible. There is no doubt it will have a large effect on anyone doing information-based work. Early AI assistants, like Copilot, already cut the time for complex tasks like coding in half. This will do the same, or more, across many industries. I think every organization that has a substantial analysis or writing component to their work will need to figure out how to incorporate these new tools fast, because the competitive advantage gain is potentially enormous. And there is no instruction manual. You can only learn through trial-and-error.

We got a glimpse of the future in the past few days, and the gap between ChatGPT (which is already causing waves in many industries) and Bing AI remains enormous. I was not expecting things in AI to keep moving this fast, but now there is every indication they will continue to do so. I don't think anyone knows what this all means, but I think we should be ready for a very weird world.

[D&NA group Tokyo @DNAgroupTokyo]

Very cool !

[Hanadi Sleiman @SleimanHanadi]

Sprinkle cyanuric acid –non-toxic molecule used in swimming pools-on DNA, and you get the strongest DNA hydrogel reported! Self-healing, stimuli-responsive, enhances gene silencing. Congrats @CLachanceBrais & all authors!
https://t.co/22BMxa3l5T
@F_ANAtico @BioinspiredMatt

[CNRS in North-East Asia @CNRSinJapan]

📢 The standard call run by @CNRS for the #JSPS #postdoc fellowship program is open!!

👩‍🔬 For young researchers wanting to stay in a laboratory in 🇯🇵 Japan
Length of stay 🌸 from 12 to 24 months
Deadline 📅 20 April 2023

https://t.co/60QaiuD8E0

[D&NA group Tokyo @DNAgroupTokyo]

Great opportunity to contribute to the future of DNA data storage !

[CNRS Sciences informatiques @CNRSinformatics]

Opportunité| J-10 pour candidater au poste de chef·ffe de projet pour assister le directeur de programme du #PEPR MoleculArXiv, dans la gestion du projet sur la thématique de recherche #stockagemoléculaire @EmploiCNRS
🗓 Deadline : 24 février 2023
➡️ https://t.co/SYAZJkwZWO

[D&NA group Tokyo @DNAgroupTokyo]

@PMMH_lab Bonjour. Ca devrait etre bon. Merci

[D&NA group Tokyo @DNAgroupTokyo]

@KawanoLab__tuat 駅伝大会頑張ってください！

[D&NA group Tokyo @DNAgroupTokyo]

@PMMH_lab Serait il possible d'avoir le lien zoom ? Merci

[good papers @paperperday]

Molecular Computation for Molecular Classification
https://t.co/DqsnOxWRcO

[Matt Henderson @matthen2]

watch a 2 layer neural network learn to separate two classes to the left and right

[D&NA group Tokyo @DNAgroupTokyo]

@YuvalElani @Deranaxel @royalsociety That was really a great event !

[D&NA group Tokyo @DNAgroupTokyo]

We were on French radio ! Thanks @ScienceCQFD @A_Beauchamp_ for this great opportunity to discuss about the potential of DNA storage.

[La Science, CQFD @ScienceCQFD]

[#Podcast] ADN : espace de stockage disponible https://t.co/XczoX3sxwK à (ré)écouter via @franceculture ! #ScienceCQFD

[Olesia Nikulina @ol_nikulina]

Academic writing is a superpower. It's a key to publishing, getting a new job or tenure, and becoming known in the field

These 10 AI-powered websites will help you with EVERY part of your manuscript and will save you 100+ hours:

#openscience #AcademicTwitter #phdvoice #phdchat

[D&NA group Tokyo @DNAgroupTokyo]

Can DNA Solve Data Storage Limits? | GEN Biotechnology https://t.co/MiGlDG6C2w

[東京大学 生産技術研究所 @UTokyo_IIS]

【記者発表】がんの早期診断等に応用可能な「分子ニューラルネットワーク」の構築 https://t.co/R2jejDKgDq

[nature @Nature]

Nature research paper: Nonlinear decision-making with enzymatic neural networks https://t.co/C7tQ0EyHGm