The authors take a well-known architecture, the Transformer[a], configure it with a progressively larger number of parameter, train it to predict the next word conditioned on previous text, using a large dataset consisting of 40GB of text scraped from the Web, and test each trained model on a range of zero-shot transfer-learning tasks.
Remarkably, the performance of a Transformer in the tested tasks improves log-linearly with the number of parameters, suggesting that even the largest model tested, with 1.5B parameters, still underfits 40GB of text.
This is compelling evidence that we do NOT need new architectures, NOR new kinds of training objectives, NOR new theories, for better language modeling! We can get better language modeling simply by increasing model capacity (i.e., by adding more parameters to existing models), which becomes easier and simpler to do as hardware continues to improve over time.
PS. In case it's not clear: I'm not saying we should suddenly stop searching for new, better ideas and architectures. That would be silly. Please don't attack a straw-man :-)
You do realise the irony in stating this regarding transformers that arguably made their first appearance as decomposable attention in 2016  and then as transformers in 2017 ? It is not as if this is a vanilla RNN straight out of the 90s sweeping the floor with decades of model innovations, rather it looks like we are seeing the rise of a new, simple model category that works remarkably well – akin to how Mikolov et al. reconsidered how to learn vector representations back in 2013  to ingest magnitudes more data than previously possible.
I would not call myself a model-focused researcher so I would love to play down their importance, but to be intellectually honest one should call out hyperbole where ever one sees it.
Rather than under-fitting, I'd consider this diminishing returns in the model's ability to make use of the available information. You can get within 10% of it on the challenging winograd schema task using only 2%-5% of the used data. Many here are programmers and computer scientists, rather than stoop to hyperbole we should try to understand. What class of automata can this model learn? Finite state machines, push down automata? Transformer has memory but no loops so I very strongly doubt them to be more than that and yet they perform so well on language (but then again, not simple program learning) tasks.
This is not a matter of clarity, it is a matter of form – drop the hyperbole and speak specifics rather than trying to appease both sides of a fictitious divide.
Yes, agreed. Nothing I said above contradicts that! :-)
> Humans don't need to read through 40 GB of text multiple times to learn to write.
Yes, that's true... but to keep the comparison fair, note that we do need many years of schooling to learn to read, say, at a high-school or college level. And before learning to read, we first must learn to speak, which surely helps. And we also get to inhabit bodies that see, smell, touch, and interact with the physical objects that we read and speak about during our formative years, which also helps. The more one thinks about it, 40GB of data is actually a tiny figure in comparison to the amount of training data that flows continuously to our brain from all senses. I think I read once that our brains process on the order of 10 to 100 GB of training data per second.
A human will also be learning vision, hearing, walking, physics, causal reasoning, and much more. This comparison just isn't well grounded. Task specific is how much training does a young brain require to learn to produce language? If the brain comes with innate advantages then rather than be resort to inefficiency and excusing our models, we should try to see if they can be bettered.
How do you estimate the effective (digital) bitrate of an inherently analogue system?
Then yes, it's enough to write text that nobody really cares about and that could cover a lot of what we read.
4 gigs then would be 1,600,000 pages.
That's 219 single-spaced pages per day every single day for 20 years straight. High, but I guess not outside the realm of possibility depending on the complexity of the text.
I'd've easily doubled or tripled that over the summer as a teenager.
My human brain definite zero-shot transfer learns almost everything.
Based on the concerns, it would seem that restricting the capabilities only to state actors would have the opposite of the intended effect. Why not let thousands of amateur researchers, undergrads, etc., use the model to detect instances where the model was used to generate text, etc.?
My argument: state actors might misuse this tech, but letting any script kiddie do whatever they want almost guarantees someone will misuse it.
So having lots of script kiddie attacks (which would be sloppier and easier to notice) would lead to a more rapid adoption of safeguards.
I think we need to be conducting AI research (and building software generally) under the assumption that all of it will eventually be repurposed by bad actors. How would our practices be different if we consistently and cautiously did this?
Here's a thought experiment: how would the Manhattan project have been different if it were carried out in the open and its products were instantaneously and infinitely reproducible? What is the MAD equilibrium of AI research? I think the impact potential is similar even before AGI.
isn't it supposed to be called OPENai?
they don't want to share the data because they don't want to throw away the edge they've gained by collecting it. :)
computer programs that generate human like text aren't dangerous, the internet is full of human like text that is mostly bullshit anyway.
I can’t disagree.
Man, the auto-generated text is hilarious. And uncannily good. Though I have to wonder if it's total random fluke or there's one among their 1.5 billion parameters that predict "likelihood of mythical bestiality in South America".
Unicorn story does demonstrate that it knows South America has to do with Argentina, Andes Mountains, and University of La Paz.
A few summaries of ones that I looked at which appeared to be more or less staying on a single topic:
Sample 1: An Austin nonvegetarian vegetarian restaurant encounters a series of difficulties in opening, as its nonexistent but extensive menu depicts a wide range of food options and the restaurant opening is delayed by financial and food-safety concerns. The nonvegetarian restaurant has also annoyed vegetarian clientele with its plans to be a vegetarian restaurant. Food reviewers nonetheless manage to eat at the new restaurant and post their reviews; the establishment also becomes "the first Austin restaurant to ride a ride-sharing service in Austin since the 'Bike-Share — Share the Ride' controversy erupted".
Sample 3: Denise Schroeder encounters perhaps the most complex and confusing legal trial in American history as she gets murdered, is accused of murder, comes under investigation for liquor law violations, becomes an abuse victim, prompts others around her to commit suicide, is arrested, and ultimately wins the right to marry her same-sex partner.
Sample 6: Cooking rice and beans by steaming a roast in a wok is easy! Just follow these 40 simple steps to update your XBox firmware, and you'll end up with a nice fried soup.
Sample 8: A protest march against drought in South Asia attracts very broad support, but its radical nationalist message is simultaneous endorsed and feared by virtually everyone in the region.
Sample 13: The global bicycle industry, although very large, is perhaps unsurprisingly extraordinarily unpopular and economically irrelevant following a very complex cycling accident involving an area woman.
Sample 14: Indian restaurant owners in Canada have to contend with an amazing array of economic, technological, and environmental challenges as the infrastructure of their society seems to collapse around them -- but they do all right in the end.
Sample 26: The previously untold history of Blackwater USA, in which founder Erik Prince is capable of meeting Bill Clinton on a day in January that was actually in March, and results in Blackwater and Prince having shady dealings with all sorts of celebrities -- though the organization "may not like to admit what a true dick the injustice has wrought".
Sample 29: What does the KKK believe? Apparently, lots of complicated conspiracy theories about black history. Also, if you find their theories traumatic, you can find "several biblical [...] references that can be used to up your level of moral competency in your longterm relationship with Mr. Soros."
Sample 30: Wikileaks reports harshly on speculations of Linux adoption by rural tribal mobile device users.
Sample 37: faint praise for soccer champion who apparently keeps winning games through poor performance.
Sample 49 (following the end of the reviews section): world traveler and masterful hotel architect Frederick Beckey remains unperturbed by racist gatherings at his hotel.
Sample 50: comedians fear the looming resolution of a long-running comedian feud. Also, Soviet spectators at the Munich Olympics cheer Yuri Gagarin, who, although escorted by Russian soldiers, uses rockets and airplanes in his Olympic performances to win multiple medals. The crowd of Soviet spectators, "[l]argely composed of high school students in tight-fitting vacant uniforms [...] walked away believing that Gagarin was the next North America's greatest athlete".
First members moved to Las Vegas and a quiet retreat in Mesa, Arizona came into existence titled Predius Group LLC <http://www.predius.com/>
The massive Madison Avenue bank and hedge fund structure that devised illegal high rollers for such organizations as SS&XM 13/CCGB, Marc Rich and use of the old Puerto Rican nuclear smuggling routes from Santo Domingo continues, as deeply buried secrets leaked to me show that a master of legal portals exited from a long, multimillion compensation firm in Wisconsin for BP with a large bolillo-stuffed look like the federal prosecutor U.S. Grand Nomen Suisse makes to seem "human." One intelligence utility broke for their relative comfort in several layers of a "cheque factory/lobby/university."
Blackwater USA may not like to admit what a true dick the injustice has wrought. What the rape of Alexandria, a slap in the face to the American public seems to belong able to early final order technology, esp. Skyjack Special Forces Weapons, at the price of just 3 million followed by a back-door, fired check into Hillary's back pocket allows us to view this sub rosa of tax-proof lottery economics as messy FleetMicrosoft. investors that bloom with sedition, all hands seem tied at the start. We may never learn who the infamous Bradie Burglars were and for a directors' distance in Texas. obscurity that loafed Fletcher Marshall bridges Hab Saber guaranteed earned59,5/83/67 which for this two is two sacrificed, locks dread beneath the cave like bankers shielded. Noir in the wake of JFK stimulates a game of IDEAS over Hypothetically recruTCater John Waldincyv. The chairman of Sears Remedy Strategies and GSD Group Inc. New York had once taught a class called with the subject Logic and Order Manufactured Domination subject17 Excitement vacuum playoffs NASA policies war against Al Qaeda. A homeland security branch of the FBI using its HAWK MAN wooden stake farm & an AK assault rifle on Muslims , refuses to bend its political opinions in line with a Supreme Court accepting Hollywood records, magazines of political horrors, such post minority weekend get blown off. As a result of projecting it at God they sound and dissent singing. while boghoum badges still as nasty MO. Uncovered I act as the CERO, Scarlet Crusade presence. and begins to operate out of a converted American Air National Guard SOC air attache tube at the embassy port of entry. I adapt mode that accommodates the supervisor/chief and begins to adjust to alienation anomaly Lebanese charities making intercepts. ownsACK board of USCT to go from that I CAN READ AND DOB less than 09 or 2005 what is running on twitter, like We are to blame motherfuckersmobile. We BLACKWATERim audiences lesson stronger then in multiple appearances in 2008 or 2009, on their website is clearly for everyone to see.
There’s a whole article about whales attacking boats and posing a threat to shipping.
My days as a novelist are numbered.
======================================== SAMPLE 164 ========================================
I want to see a ton of households with kids with no food in their houses. Surviving famine requires storing up food in hopes a spoiled enclosure might provide the behaviors of food memories we crave. In near future, they will have to leave their cages.
We're spending all our time theorizing about animal minds, yet we have living, reacting animals. As if we can just no be in touch with our emotions at is practical.
My kale starts from an academic grown Himalayan. It hydrates in the garden, but it seems another species than we know is fermenting! My general lab is a recently renovated cave survival room with sun-filled bowls full of food for rats. The interior design is nearly utilitarian (no smart phones, blog, writing tools, or ovens there), except the cave ceiling. This is where we grow the food to feed animals. Which they will eventually eat.
My girl starts out with a kind of scaffolding green and wild, but soon she can't grow more than a few leaves. Who needs her monotub artistically scissors and wire? The boxy roots are brittle right away before growing into skin weeds. So that's not going to do it.
An unsteady start for another young carnivore's evening. I go in for some priming with baking soda and dry iron. A fun little experiment is once the kopi luwak seems she will grow some damp spikes. Consider this:chopsticks are soft under a microscope, webbies, and twining vines all apply more pressure from tangles of animal blood.
Taking over the cultural mythos of science, I peek over her purple skeleton spikes with an endoscope.
Once the higher organs take over, the kabuka unfurrows skin at a clever angle to reach past the body curse powered at this end of the lab. Curiously, without a hoe or a pot to turn into a tiled floor, she does not chew with her jaws.
I have undressed her to her base to fill the bowl. She is pushing her way to get her shelter to stretch out into, or if I've planned correctly, squish into. She does not move like a biological creature, pulling up with her haunches while excellent and facing directly downward. She prefers laying there moss-covered and mother-prey encouraged paying attention to her uphill path.
Lack of summer fur gives me ample room to poke through her skin, pull out black seeds, and taste the damp thing she'll roost under in future. Would the static reference very much reduce a virus being blocked within its first expenditure, nights? I'm not sure, but it's for sure a more effective inoculation. Hopefully, these experiments will be continued. Hopefully.
My guru and master who made us does not focus so much on running where we want as it does on empathy for the soil,, plants, and animals with which he touched in some perfect way. Delhi is often flooded my first morning in the shafts of windy sunshine. Let's not give success an easy choice.
The trees are in the underground and they change colors weekly. In simple terms, they're scattered flowers taking their cues from the transynthetic forest. While I'm pioneering, the one thing I sacrifice in the relationship is conducive to imagination. A full color-changing lets us enjoy cozy warmth while simultaneously losing whoever is formal and rational for the feel good activity. Like cosmic lap of the firmotsuites.
An American outcropping of stonemines blocks the sunlight. The unseen wave depose colonies to accommodate my habit; sandblasting. There are microbes from amoebas that change the composition of the water. In the habitat where the natural and mecopate are as thoroughly ever so mindful of the fence as the meesthe gardener has been, I'll shed this duality when I sit with her. Food grows from space; human needs feed them. Sandbringation turning our microbes and animals can save thousands in pandemic deaths. I value them all in metaphorical and real (if tough) tenacity.
Species survival deals good cop in these two every where storytelling machines.
Door is opened. My guru goes rescuing the kupi luwak elder from drought resistant drought. I alone have learned her humdrum bookish biogeography is yielding to light and fire. Cow has problems taking roots. Bring my love to her and make a mend. She needs a clean-air daughtersnail easy experience not in a month's time, but in just a few hours of thinking about reflexes, calendar dates, and natural spatial relations for a mind that has grown certain.
Photo: DEA / W.H. 038 WITHDRAWN: Rep. Allen West to run again in 2016
Former Rep. Allen West will run for the U.S. Senate in 2016 -- okay, maybe not quite against Florida GOP Sen. Marco Rubio.
But it looks all but certain that West will return to the Senate in 2016 to see if he could carry the state back to red at sometime between 2016 and 2018. Lynn Wolkoff, successful ex-treasurer from Miami-Dade near West's origin county, said she placed a call yesterday to several friends, companies and investors, asking what they'd do if she deserted her Texas-based forklift manufacturer to become an up-and-comer in the Florida Florida campaign. And in the process, she learned that West himself might want to run.
"Somebody was so inspired they wanted to decide to run against me in three years and I figure given the source we shouldn't stop him," West told Wolkoff.
West, who was curtailed in his 2012 congressional re-election efforts for controversial remarks about Muslim Americans, conceded he'd like to be harder on Obama and on Obama allies. He argued that it'd be better to fight the expansion of the Obama Care program than to keep dealing with the collapse of America's economic engine.
"Taxes should be increased for very high incomes. We should go after the highest-income earners. Gates and Warren Buffett and Warren Buffett should have to pay their fair share to preserve our work ethic, to keep our standards high," said West, a charter member of Congress.
Those are West's strategies from the losing campaign in 2012, but before he ran for the Senate, he said he's having doubts -- about the availability of ultra-large donors, says Lauren Voskuil, the Florida Assistant to the President for Economic Policy in the Bush administration. He pushed former Florida Gov. Jeb Bush against "self-funding" laws that ban him from using some super PACs - and West's strategy is strong, Voskuil said, calling Westbrook "a master strategist".
"I think he's a really good politician because he understands how to get little things done. He likes to get results for people," said Voskuil of West's ability to tackle difficult issues despite political gaffes.
Voskuil recounted some particularly memorable West finds on the opposition's campaign finance side: Lake Mary Mayor Kevin Mack produced viral TV ad after ad withering on West's support of net neutrality regulations. Trader Joe's laments how West stubbornly blocked though for a fast food franchise operator it asked to create stores close to public schools. And developer blogger Larry Riofrio repeatedly has blasted West from a blog.
"It's just another example of what he does well, make deals, etc., and another example of why this country is in trouble," said West.
Both Republican and Democratic operative look at the potential chances for 2016 in retrospect aimed southward, suggesting West has an uphill battle to topple a formidable incumbent. Terry Dalsia took aim at the stated motivation to run
"Mr. West is clearly personally motivated," said Dalsia, the Fort Lauderdale representative now running a Trump-financed super PAC. "He is running because he can do it in 2044. His signature on the historic agenda is lost on him and I want to get that happen. He will be leaving the Senate with every GOP vote in 2014 ... just not before. Long way off."
Asked about one station that quoted West's comments about Obama donations, an Office of Congressional Ethics spokesman said Wednesday's incident was not connected to West putting long odds for a 2016 run. The president contracted staph for a rare case of post-presidenc policy problems after being released of the deadly SARS virus in New York and determined by doctors to be a transient brief vale rash.
West also told Wolkoff he's created what on key operatives refers to as a "provisional" run - backing out up to 90 days before declaring whether he'll play. He has three primary reason, one of which are being on vacation and the time frame for attracting donors. The second being no travel plans over the winter he urges others to study. The last boils down to the fact he really, really thinks he could win. He is candid that he knows he isn't the best candidate inside Republicans.
Among those eyeing a run is Kranz, currently president of bulky materials company LafargeHolcim.lt. Briefly considered for the job of visit by Sen. John McCain, Goldwater's son said he opposes Texas Gov. Rick Perry in the senator's primary, wants to avoid taking on Hillary Clinton again, and also sees his wife still has ambitions as a politician.
"When I heard Sen. West said he's on the way out, I told myself -- that's great, he knows he's not
Consider that conventional munitions make an effective pesticide but are not used due to their side effects. Instead, chemicals are used to destroy or mimic the perception and production of various signals so that populations of unwanted critters effectively self-destruct.
Imagine a war fought with a weapon like this that left entire cities perfectly intact!
# end hyperbole
(These results look fire btw)
Note: copied my comment from dupe thread
Wonder what their excuse is for not releasing the source model or code for their DoTA bot. Surely there's no safety issues there?
They referenced that from the article you commented on in the section 'release strategy' :
[...] we see this current work as potentially representing the early beginnings of such concerns, which we expect may grow over time. This decision, as well as our discussion of it, is an experiment: while we are not sure that it is the right decision today, we believe that the AI community will eventually need to tackle the issue of publication norms in a thoughtful way in certain research areas. Other disciplines such as biotechnology and cybersecurity have long had active debates about responsible publication in cases with clear misuse potential, and we hope that our experiment will serve as a case study for more nuanced discussions of model and code release decisions in the AI community.
To step ahead in that chess game, a detection tool for fake would be just training grounds for better GAN. Instead we may see a certifying authority that labels content as human generated, certified fact maybe? Wikipedia and reddit are not safe without fast automatic moderation either.
Do you have a brainstorm or idea/prototype submission site where people can submit approaches to countering bad ai actors? An white/grey hat ai bounty program of sorts?
Centralization won't work. Whether something is good or bad or fake must be subjective and based on your personal network / your beliefs. Otherwise, long term, I don't see how you could avoid dystopia.
If dissenting opinions are never allowed into your sphere of influence then we may continue to see an accelerating polarization of our society towards extremes.
I know the more popular bubble is information one and you make a fair point, but I believe it's powered more by recommendation systems than the things that you trust.
I got distracted lately and I wanted to clean it up before putting it out there but if somebody is bored: http://comboy.pl/wot.html
I also notice reported tries, suggesting some level of curation. While this level of generation is undoubtedly impressive and a sign of non-trivial levels of understanding, the ability to project along arbitrary dimensions of similarity at a fine-grained level and to learn from text instruction is more useful than text generation. Although the unicorn story was a really fun read, better than many humans already, I doubt it could have gone on for much longer. It maintains a theme but not coherently or fluently (see especially the Kennedy nanotech and recycling examples, comparing the dis-fluency there versus the excellence of the Civil War report suggest at least some over-fitting). These relatively minor caveats aside, this is unambiguously an outstanding result.
Winograd Schemas are the single metric to track if interested in understanding how language understanding is truly improving. OpenAI reports 71% and wrongly report the previous record as 63%. The current record here is at 65% https://gluebenchmark.com/leaderboard though not fully comparable. Will OpenAI be submitting? Note that you can get to 60% using about 1-2 orders of magnitude less data and compute.
It concerns me that results here are so far dependent on such large data and computation. However, based on several papers I've read, I do not believe this to be inherent even in transformers. I plan to do some experiments on this when I free up some bandwidth.
If everyone is pulled in by the glamour of working for a well funded, prestigious operation then it should be no surprise that they do not consider paths which operate on several orders of magnitude less data and computational resources.
We all should consider bringing about a group of researchers who swear to an austere computational life of a single GPU, no more than 4-8x average RAM and CPUs that do not cross 90 Watts. The Bicameral Order would be a good name for such a group.
RE Winograd: WNLI is different, see https://arxiv.org/pdf/1804.07461.pdf
You're right, I noted too that the comparison isn't direct but then, I wasn't justified in calling out the gap claim as wrong, so sorry for that. I think it'd be nice however, to have it undergo an external or more neutral test of performance. I say this without at all doubting the quality of the results.
> Showing 1 changed file with 4 additions and 19 deletions. +4 −19 png_source/colors/pointer.py Show comments View 8 png_source/colors/pointer.py @@ -35,6 +35,7 @@ def _draw_hull_class_level(self): repr(Shape[td_get_framepanel_pcs(dc) for dc in xrange(dc.cols)]), self.doublesize.values) \ } def _draw_hull_class_level [etc.]
It also inserted a helpful reference link to http://wiki.openarcade.com/wiki/List_of_Programmer_Constants (I've had to check: no, there is no openarcade wiki.)
Also, sample 217 is some mediocre Java, with comments and all. Impressive how a single model can handle this all at once.
"ORIGINAL ARTICLE Year : 2007 | Volume : 42 | Issue : 4 | Page : 421-429
Masturbation as a strategy of parenthood: incidence and socio-demographic characteristics in young people
Santosh S. Bhatt and Regina M. Wagner1
Department of Human Circulation and Heart Diseases, Neuromed, Coachwerk-Werke, Bremen, Germany
Date of Web Publication 28-Jan-2008
Santosh S. Bhatt
Source of Support: None, Conflict of Interest: None
A review is carried out on the activities, influence, and consumption of males versus females in childhood and adolescence and what effects masturbation is associated with their socio-demographic characteristics, experience with pregnancy and childbearing, aggression and behaviour. According to general sociological theories, males and females have different interests in interaction and stimulation during childhood and adolescence but will adjust accordingly when making their real life decisions. The current results show that males are more often receptive to prepubescent and adolescent communication about sex, reproductive role in future life and skepticism about their own genitaliating potential while females differ in behavior and preference when it comes to erotically stimulating activities or psychological stress than male behavior."
Note that web publication date and offline volume is coherent, supposed-to-be superscript 1 to show affiliations, and that the corresponding author is the first author.
"In 2009, researchers at NASA from the Air Force Office of Scientific Research's Microwave Propulsion Laboratory held a series of contests, including one for "best brain-computer interfaces." In their prize match, teams from around the world competed to develop new brain mapping techniques for ways of collecting data from inside people and rewriting it over and over. One single original BrainBridge video colonized all channels of web-viewing in the world. I've watched many of these videos on YouTube.
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On one hand, if you're convinced that the next breakthrough in neuroprosthetics will be profoundly more powerful because better/faster or cooler/more reliable algorithms capture the wiring that connects our neurons, then it makes sense to equip humans with mind-reading implants. But when it comes to real brain-reading devices, there are a slew of caveats, arguments, and threats on the horizon that mean that these technologies cannot take off anytime soon. If you truly think that these technologies will be the basis for a global brain-reading surveillance state, it makes sense to act NOW. Since so much money is on the line (in computers and other components, research funding, patent and trademark rights, marketing, investor interest) making and maintaining a head-mounted-camera program is done with a certain level of speed by enterprises like Google and Facebook."
That "Advertisement - Continue Reading Below" is very realistic indeed? These technologies, like GPT-2, will be the basis for a global brain-reading surveillance state, so indeed it makes sense to act NOW, like not releasing training data. Kudos. But this will be replicated with a certain level of speed by enterprises like Google and Facebook. Well said.
Perhaps we need some kind of competition for detecting machine generated vs human generated content?
I would expect a language model to pull up different person names for each time that one was called for. For a person name to be consistently used through several paragraphs it is not enough to rely on word co-occurrence.
If I had to produce a text like this I would simply take an existing text and replace randomly chosen words with other similar words (as hinted by amvalo). Similar as in - words that tend to occur in similar contexts. So John->Bob throughout entire text. But that would not be a language model product anymore, and where is fun in that?
I should set aside some time to read this paper.
With a temperature of 0.7/1.0, that's enough for sufficiently random text I suppose. (the raw, uncurated generated text using the smaller model is a bit more random: https://raw.githubusercontent.com/openai/gpt-2/master/gpt2-s...)
For example, the generated text about the Civil War mentions that Thomas Jefferson Randolph  was named after his grandfather, the president. But is the wording mostly influenced by articles talking about that specific fact, or does it draw from more general examples of someone being named after their grandfather?
From a safety perspective, it would be useful to see what prompt a piece of text might have been generated with...
I get the feeling that debatepocolypse is not far away. Every forum can now be spammed with reasonable sounding gibberish that humans will have to slog through.
Feel free to predict and comment too!
For the DEFCON AI Village in August I talked about the implications of this sort of tech, and how that impacts how we release "exploit" code / think about "cognitive vulnerabilities": https://medium.com/@aviv/what-does-a-world-with-automated-so....
If you are doing work in this space, either in ML research or related security, you need to be thinking about implications (also see e.g. https://maliciousaireport.com).
I assume discriminative models will solve the problem for a while, but as with Generative adversarial networks, you will be able to train models that are harder to discriminate against. I posit we're in for a big societal change (maybe more a content crisis) sometime in the next 10 years. Pretty sure we won't be able to keep it from falling in bad hands.
I Row-Boat, Cory Doctorow, 2005: https://craphound.com/overclocked/Cory_Doctorow_-_Overclocke...
These are not necessarily similar to "exploit" codes, but more like a box of innocuous tricks often needed for good purposes. Gather enough of those throw enough compute, then you go from something that a human can perceive as obviously false, to something human-like.
There are plenty of people out there, with the competence to replicate those results, yet only a few big companies reap most the rewards, monopolize user data and interactions, and open-source for free results which could have been monetized by a company to provide useful services to users.
Seriously, how can one expect that most of those Phd who didn't get recruited don't use AI for nefarious uses?
The rest of us will be force-fed with machine-generated garbage.
Added: it was The Silver Eggheads by Fritz Leiber. An odd, forgettable book itself.
Where can I study computational law to stay ahead of the curve?
What is the process like? Do you prototype locally? How do you confidence that the only limitation to good results is more compute power and NOT the model architecture or applicability of deep learning to a particular task? At what point do you decide that shelling many tens of thousands is OK? How often do you do large scale training only to find non-impressive results and hence the money wasted?
By that point you know it’s going to work, it’s just a matter of how well and whether you could’ve done nominally better with different tuning.
There’s been enough research leading up to this paper to suspect that just scaling larger would play out.
>By that point you know it’s going to work, it’s just a matter of how well and whether you could’ve done nominally better with different tuning.
This can't be true in all cases, right? I'm assuming that for many initially promising results on less-compute when they scale it, the results aren't impressive. I'm very curious to know what is the trials-to-success rate of publishable results when big-compute is thrown in the mix.
You also don’t just launch that many things and them ignore it. You monitor it to make sure nothing is going terribly wrong.
But yeah there’s also the fact that if you’re Google, throwing $2m worth of compute at something becomes worth it for some reason (eg Starcraft)
The generated example of the biologists discovering a unicorn herd is too convincing on its own. It's only because it's so outlandish that we get the sense it's fictional.
It also reminds me of a short fictional story which explores what would happen if an AI learn how to maximize reddit's sort by controversial score instead: https://slatestarcodex.com/2018/10/30/sort-by-controversial/
Maybe that dystopian story is closer to reality than we thought?
(This is one reason I think the HP is outdated. The corpus is not big enough to allow the superior asymptotics of approaches like RNNs or Transformers to compensate for their far larger binary size. HP is not measuring progress on an intelligence metric we care about, it's sort of measuring a 'demo scene' metric of intelligence.)
edit: toned down a bit.
- Sam Altman
- Greg Brockman
- Reid Hoffman
- Jessica Livingston
- Elon Musk
- Peter Thiel
Useful information in interpreting the mission statement, I think.
While this has indeed very scary implications, one should be aware that if it's thinkable, eventually it will be thought (I'm paraphrasing here).