further reading
The selection of sources suggested by this text is impressively wide and good.
further reading
The selection of sources suggested by this text is impressively wide and good.
this is a serious problem because all they need to do is automate AI research 00:41:53 build super intelligence and any lead that the US had would vanish the power dynamics would shift immediately
for - AI - security risk - once automated AI research is known, bad actors can easily build superintelligence
AI - security risk - once automated AI research is known, bad actors can easily build superintelligence - Any lead that the US had would immediately vanish.
Sam mman has said that's his entire goal that's what opening eye are trying to build they're not really trying to build super intelligence but they Define AGI as a 00:24:03 system that can do automated AI research and once that does occur
for - key insight - AGI as automated AI researchers to create superintelligence
key insight - AGI as automated AI researchers to create superintelligence - We will reach a period of explosive, exponential AI research growth once AGI has been produced - The key is to deploy AGI as AI researchers that can do AI research 24/7 - 5,000 of such AGI research agents could result in superintelligence in a very short time period (years) - because every time any one of them makes a breakthrough, it is immediately sent to all 4,999 other AGI researchers
having an automated AI research engineer by 2027 00:05:14 to 2028 is not something that is far far off
for - progress trap - AI - milestone - automated AI researcher
progress trap - AI - milestone - automated AI researcher - This is a serious concern that must be debated - An AI researcher that does research on itself has no moral compass and can encode undecipherable code into future generations of AI that provides no back door to AI if something goes wrong. - For instance, if AI reached the conclusion that humans need to be eliminated in order to save the biosphere, - it can disseminate its strategies covertly under secret communications with unbreakable code
The nightmares of AI discrimination and exploitation are the lived reality of those I call the excoded
AI raises the stakes because now that data is not only used to make decisions about you, but rather to make deeply powerful inferences about people and communities. That data is training models that can be deployed, mobilized through automated systems that affect our fundamental rights and our access to whether you get a mortgage, a job interview, or even how much you’re paid. Thinking individually is only part of the equation now; you really need to think in terms of collective harm. Do I want to give up this data and have it be used to make decisions about people like me—a woman, a mother, a person with particular political beliefs?
Staff and studentsare rarely in a position to understand the extent to which data is being used, nor are they able todetermine the extent to which automated decision-making is leveraged in the curation oramplification of content.
Is this a data (or privacy) literacy problem? A lack of regulation by experts in this field?
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It’s tempting to believe incredible human-seeming software is in a way superhuman, Block-Wehba warned, and incapable of human error. “Something scholars of law and technology talk about a lot is the ‘veneer of objectivity’ — a decision that might be scrutinized sharply if made by a human gains a sense of legitimacy once it is automated,” she said.
Quote by Hannah Bloch-Wehba, TAMU law professor
This model was tasked with predicting whether a future comment on a thread will be abusive. This is a difficult task without any features provided on the target comment. Despite the challenges of this task, the model had a relatively high AUC over 0.83, and was able to achieve double digit precision and recall at certain thresholds.
This is fascinating. The model is predicting if the next, new comment will be abusive by examining the existing conversation, and doing this without knowing what the next comment will be.
And therefore, to accept the dictates of algorithms in deciding what, for example, the next song we should listen to on Spotify is, accepting that it will be an algorithm that dictates this because we no longer recognize our non-algorithmic nature and we take ourselves to be the same sort of beings that don’t make spontaneous irreducible decisions about what song to listen to next, but simply outsource the duty for this sort of thing, once governed by inspiration now to a machine that is not capable of inspiration.
The growing prevalence of AI systems, as well as their growing impact on every aspect of our daily life create a great need to that AI systems are "responsible" and incorporate important social values such as fairness, accountability and privacy.
An AI is the sum of its programming along with its training data. Its "perspecitive" of social values such as fairness, accountability, and privacy are a function of the data used to create it.
Chongthanavanit, P., Kennedy , J. M., & Kheokao , J. | Thammasat Review | Vol. 23 No. 2 (July-December) 2020 287 Figure 5 A Screenshot of Automated Sentiment Analysis
Automated Sentiment Analysis
In practice, we usually also need another tool to provide an API to control the browser (e.g., ChromeDriver).
“System tests” is a common naming for automated end-to-end tests in the Rails world. Before Rails adopted this name, we used such variations as feature tests, browser tests
This poses a few problems for automation. In some environments, there may be no graphical display available, or it may be desirable to not have the browser appear at all when being controlled.
Keeping bootstrap-sass in sync with upstream changes from Bootstrap used to be an error prone and time consuming manual process. With Bootstrap 3 we have introduced a converter that automates this.
Because of those similarities, it's possible to automate some of the changes.
This needs to be documented (issue in webpack/webpack.js.org will be filed when merged)
the actual upgrade path should be very simple for most people since the deprecated things are mostly edge cases and any common ones can be codemodded
(At the point at which it does make sense to turn this into a separate Tooltip.svelte component, the extraction is a completely mechanical process that could even be automated by tooling.)
Motta, M., Stecula, D., & Farhart, C. E. (2020). How Right-Leaning Media Coverage of COVID-19 Facilitated the Spread of Misinformation in the Early Stages of the Pandemic [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/a8r3p
Virtual MLSS 2020 (Opening Remarks). (2020, June 29). https://www.youtube.com/watch?v=8staJlMbAig
Zdeborová, L. (2020). Understanding deep learning is also a job for physicists. Nature Physics, 1–3. https://doi.org/10.1038/s41567-020-0929-2
It’s important to note that where the GDPR applies, intended use factors into whether or not consent is required as even statistical data can fall under “profiling” or “monitoring” depending on how the data is being used.
I originally did not use this approach because many pages that require translation are behind authentication that cannot/should not be run through these proxies.
It shouldn't be problem to watch the remote scripts for changes using Travis and repack and submit a new version automatically (depends on licensing). It does not put the script under your control, but at least it's in the package and can be reviewed.
In case you’re implementing any ADM process, you have to tell your users.
Some languages are crowd-sourced with free labor, and they make money out of it.
You might try this extension: https://github.com/andreicristianpetcu/google_translate_this It does the same thing in the same way as Page Translator and likely will be blocked by Mozilla, but this is a cat and mouse game worth playing if you rely on full-page in-line language translation.
For automated testing, include the parameter is_test=1 in your tests. That will tell Akismet not to change its behaviour based on those API calls – they will have no training effect. That means your tests will be somewhat repeatable, in the sense that one test won’t influence subsequent calls.
Global industrial robot sales
First sighted at: https://github.com/neutrinojs/neutrino/pull/1003
With SmartBooks, students can see the important content highlighted
Like an algorithmic version of Hypothesis? Is McGraw-Hill part of the Coalition? Looks like it isn’t. Is it a “for us or against us” situation?
Open Source[edit] LightSide[43] EASE[44] - Published by EdX.
Open Source software for Automated Essay Scoring
Alternatively, Daphne Koller and Andrew Ng who are the founders of Coursera, a Stanford MOOC startup, have decided to use peer evaluation to assess writing. Koller and Ng (2012) specifically used the term “calibrated peer review” to refer to a method of peer review distinct from an application developed by UCLA with National Science Foundation funding called Calibrated Peer Review™ (CPR). For Koller and Ng, “calibrated peer review” is a specific form of peer review in which students are trained on a particular scoring rubric for an assignment using practice essays before they begin the peer review process.
A rigorous understanding of these developmental processes requires automated methods that quantitatively record and analyze complex morphologies and their associated patterns of gene expression at cellular resolution.
Rigorous understanding requires automated methods using quantitative recording and analysis.