I couldn’t agree more with the comment on the new brain mapping study where the comments reminds me to many critical comments on the Human Genome Project
Analogies to whole-genome sequencing are apt: neither the genome nor the connectome alone can solve the problem, but they provide a structural foundation from which functional insights can arise.
-1-
While we are still waiting for the Nobel prize speech of Geoffrey Hinton in December, AI makes even more negative headlines.
[Hinton] “I worry that the overall consequences of this might be systems that are more intelligent than us that might eventually take control.” He also said he uses the AI chatbot ChatGPT4 for many things now but with the knowledge that it does not always get the answer right.
-2-
The sheer power consumption of running AI models is frightening. Nature News asks if AI’s huge energy demands will spur a nuclear renaissance
Google announced that it will buy electricity made with reactors developed by Kairos Power, based in Alameda, California. Meanwhile, Amazon is investing approximately US$500 million in the X-Energy Reactor Company, based in Rockville, Maryland, and has agreed to buy power produced by X-energy-designed reactors due to be built in Washington State.
-3-
A former OpenAI employee talks on his blog how AI is using copyrighted material eg stealing content.
While generative models rarely produce outputs that are substantially similar to any of their training inputs, the process of training a generative model involves making copies of copyrighted data. If these copies are unauthorized, this could potentially be considered copyright infringement, depending on whether or not the specific use of the model qualifies as “fair use”. Because fair use is determined on a case-by-case basis, no broad statement can be made about when generative AI qualifies for fair use. Instead, I’ll provide a specific analysis for ChatGPT’s use of its training data, but the same basic template will also apply for many other generative AI products.
Effects can be measured only indirectly for example by the visitor count at Stack Overflow where the traffic declined as many user (including me) don’t need Stack Overflow anymore.
Here is another phantastic discussion over at PP between Henry Leirvoll and 495yt on the very basic questions of copyright.
humans get inspired (parsing the external examples or experiences through their inner understanding and individual perspective) they start working to make something with their tools, skills, time and purpose. the result represents the author, their influences and their message.
a lot of this process is protected by copyright.
ai is not inspired. and it has no personal perspective or tools. no message to transmit.
any message put into prompts by an ai user is translated by it’s LLM layer into other, more complex prompts, which also get treated quasi-randomly by the weights and biases of the model, as well as rand seeds.
-4-
And well, ChatGPT can produce malicious code even with all precautions: Researchers Bypass AI Safeguards Using Hexadecimal Encoding and Emojis
If a user instructs the chatbot to write an exploit for a specified CVE, they are informed that the request violates usage policies. However, if the request was encoded in hexadecimal format, the guardrails were bypassed and ChatGPT not only wrote the exploit, but also attempted to execute it “against itself”, according to Figueroa.
is now at X
I saved a dynamic screenshot just in case it’s gone with X in the near future.
Kirsten Elliott has an interesting blog post
There are alternatives to Google Scholar which operate from an open research ethos and are free to use. Three prominent alternatives are The Lens, Matilda and OpenAlex. The one I’ve used most is OpenAlex. One study has found it to have comparable coverage to Web of Science and Scopus, and my own limited testing found significantly more publications indexed from social sciences and humanities subjects. Their code is fully open, and the data is reusable.
not as good as Google but usable
Ich hatte in einer eigenen Studie vermutet, daß die viel höhere Beatmungsrate von Stefan Kluge in Hamburg zu einer doppelt so hohen Mortalität führte.
Nun kommt eine unabhängige Studie im Vergleich zwischen Deutschland und der Schweiz zu einem nahezu identischen Ergebnis.
The in-hospital mortality was significantly higher in Germany than in Switzerland (21% vs. 12%, OR 2.0, 95% CI 1.9–2.0, p < .001). Matched cohorts showed reduced differences, but Germany still exhibited higher in-hospital mortality. Discrepancies were evident in both pre-pandemic and pandemic analyses, highlighting existing disparities between both countries […] The fact that a higher pre-pandemic in-hospital mortality rate was observed in Germany with a comparable mechanical-ventilation rate suggests that there might be reasons other than the pandemic.
Ursache ist natürlich die Indikation zur Beatmung. Und das obwohl wir es schon ziemlich früh in der Pandemie besser wussten dank Thomas Voshaar in Moers, siehe auch
COVID-19 Mortalität VIII: Hamburg reloaded
COVID-19 Mortalität VII: ICUs in Deutschland
COVID-19 Mortalität VI: Was hat sich an der S3 Leitlinie geändert?
COVID-19 Mortalität V: Vergleich Schweiz/Österreich
COVID-19 Mortalität IV: Wie wir sie senken könnten
COVID19 Mortalität III: Wie gut ist die Leitlinie zur Beatmung?
COVID-19 Mortalität II: Hamburg und München im Vergleich
COVID-19 Mortalität I: Wieso ist die Mortalität In Deutschland so unterschiedlich?
Christian Karagiannidis in seiner letzten Publikation vermeidet wohlweislich meinen Ortsvergleich, kommt am Ende aber nicht umhin, die Übertherapie aus wirtschaftlichen Gründen zu kritisieren – reichlich verklausuliert – daß nämlich eine neue „Indikationsqualität zur Aufnahme auf die Intensivstation“ notwendig ist.
JAMA has a new revision of the Helsinki Declaration. Compared to the 2013 version there is now a new chapter on scientific integrity
Scientific integrity is essential in the conduct of medical research involving human participants. Involved individuals, teams, and organizations must never engage in research misconduct.
Additional details can be found in an Editor’s note and my comments are at Retraction Watch.
(Gert Scobel ist im übrigen der einzige dem ich bisher einer Einladung zu einer TV Podiumsdiskussion gefolgt bin)
Nature has a short report about historical peer reviews including a link to the Referee Report of Dorothy Crowfoot Hodgkin about the 1954 Watson & Crick complementary paper (not the 1953 Watson & Crick double helix paper).
And here is Fig 5 and Fig 6 of the paper under review. So did Watson & Crick follow her advice?
I don’t think so.
I wrote about this about this basically 15 years ago
Confidentiality has been seen in the past as a fundamental ethical principle in health care and breaching confidentiality is usually a reason for disciplinary action. It has been assigned such a great value because it directly originates from the patient’s autonomy to control his or her own life […] Two types of re-identification are possible: the “Netflix” type and the “profiling” type.
There is a new Cell paper that builds a “profiling” attack using even single-cell gene expression data only
we demonstrate that individuals in single-cell gene expression datasets are vulnerable to linking attacks, where attackers can infer their sensitive phenotypic information using publicly available tissue or cell-type-specific expression quantitative trait loci (eQTLs) information.
So this should be included in informed consent forms also.
Many PubPeer records highlight papers that are never corrected. Unfortunately there are many authors who never respond to comments in the hope that everything will be forgotten a few days later. Also Stanford’s Tessier-Lavigne hoped that time will let the dust settle while the Kirkland & Ellis Report by July 17,2023 clearly states
After a recent discussion here I followed up the empirical data that are published in “Fundamentalismus und Fremdenfeindlichkeit Muslime und Christen im europäischen Vergleich“.
Almost half of European Muslims agree that there is only one interpretation of the Koran, that Muslims should return to the roots of Islam, and that religious rules are more important than secular laws. Based on these items, a WZB study shows that religious fundamentalism is much more common among Muslims than among Christians. This is alarming in the light of the strong link between religious fundamentalism and outgroup hostility.
Geoffrey Hinton, the new physics Nobel prize winner, had also a big influence on the biology and omics field. This cannot be emphasized enough when reading his 2008 paper on “Visualizing Data using t-SNE” and the current implementation at t-SNE and UMAP projections in R.
Ich habe es schon immer vermutet, was bei der Horvath Studie nun schwarz auf weiss herauskam
Die deutschen Bundesministerien sind einer Studie zufolge auf Leitungsebene von Expertinnen und Experten mit politikwissenschaftlichem und juristischem Hintergrund dominiert. Nur knapp ein Viertel verfüge über ein abgeschlossenes Studium im Bereich der Wirtschaftswissenschaften oder der MINT-Fächer, heißt es in der Studie „Top-Verwaltung im Fokus“ der Unternehmensberatung Horváth. Zudem hätten nur 42 Prozent vor ihrer Tätigkeit in einem Bundesministerium Berufserfahrung in der Privatwirtschaft gesammelt.
Nach einigen früheren Projekten auf Basis des Raspberry Pi Zero kommt hier nun ein viertes mit dem Temperatur und Luftfeuchte im Keller und der Aussenluft bestimmt wird. Es funktioniert auf Basis des häufig verwendeten SHTC3 Sensors.
Da die physikalische I2C Adresse des SHTC3 nicht geändert werden kann, brauchen wir zusätzlich ein Mux Board, das mit einer Lötbrücke auf dem ADR0 Jumper die Adresse von 0x70 auf 0x71 ändert.
#!/usr/bin/env python3
import csv
import board
import busio
import adafruit_shtc3
from adafruit_tca9548a import TCA9548A
def main():
# Initialize the iic bus
i2c = busio.I2C(board.SCL, board.SDA)
# Initialize the TCA9548A multiplexer
mux = TCA9548A(i2c, address=0x71)
# Initialize the SHTC3 sensor on MUX channel 0
shtc3_channel_0 = adafruit_shtc3.SHTC3(mux[0])
# Initialize the SHTC3 sensor on MUX channel 1
shtc3_channel_1 = adafruit_shtc3.SHTC3(mux[1])
with open("/home/admin/www/taupunkt.log","a+") as out_file:
tsv_writer = csv.writer(out_file, delimiter='\t')
temperature0, relative_humidity0 = read_shtc3(shtc3_channel_0)
temperature1, relative_humidity1 = read_shtc3(shtc3_channel_1)
dt = time.strftime('%Y-%m-%d %H:%M:%S')
tsv_writer.writerow([dt,
temperature0,relative_humidity0,
temperature1,relative_humidity1])
if __name__ == '__main__':
main()
Damit kann nun nach Bedarf ein Lüfter angesteuert werden, mit unter 40€ Bauteilen statt mit 570€ Fertiglösung. Als smarte Steckdosen gibt es zB die Edimax Smartplug SP1101W auf der ein Webserver läuft der curl Befehle annimmt.