Tolkien Untangled with Poems, Songs, and More Video References

LOTR - Middle Earth Music & Ambience

(intended to be played when reading all that is set below)

3 hours

Being the last day of 2022 I wish to remember the poems and songs of JRR Tolkien speaking of love and lost, wander and thrall. Within the sad tales of Middle Earth comes bred upon the human breast a wistfulness for better days when fellowship no longer strives with ruin and evil. Where the grand majesties set deep upon the hearts of all beings cannot undo themselves by heavy lost but finds within a deeper courage and longing to aright wrongs done and all be redeemed by torn atoning struggles for peace and justice founded upon the shattered halls of love unremitting its trials and longings.

R.E. Slater

December 31, 2022

@copyright R.E. Slater Publications

all rights reserved

link to

INDEX - History of Tolkien's Middle-Earth

Rendition of Middle Earth with enlargement link

Middle Earth before and after the First Age

Elven Lands of the First Age

Elven Realms of the Third Age

The Elven Kingdom of Lothlorien

Within the Halls of Lothlorien

Rendition of Rivendale

Rendition of Rivendale

The Lays of the Grey Havens

"The LOTR is not about power and dominion

but about death and deathlessness." - JRRT

"Under the fading trees the land was silent." - Elven Lady Arwen

Lady Arwen, upon leaving the side of her Thrane and husband, Aragorn, and the whiten fortresses of Gondolin - where lay his tomb in the Hallows of Minas Tirith - thence journeyed onwards across Middle Earth to Lady Galadriel's remembered forest realms of Lothlorien. Then onwards to her Elven father Elrond's hidden realms founded upon the rocky chasms of Rivendale. And therefrom her father's lands Arwen thence turned westward towards the greensward troves of the misty Grey Havens once abounding it's vast inland and coastal realms under the tendering care of Elvish hands. Yet thereto did Arwen behold the fey wastelands conscripted in deeper losts than its lores and legends. For all she surveyed leaned upon her heavy heart the fast retreats of man's fourth age whose rule and imagination languished before her renown predecessor's gifted domains once wrapped in light and life within the deep and purposeful care of their Elven lord's faded dominions. - R.E. Slater

For Tolkien, as for his magical realms of lore and wisdom, time may be slowed but never stopped. Vast realms and traditions, cherished friendships and places, may for a time be preserved and protected yet all will eventually succumb to death and soulful reprocessing into the unknown realms beyond death's fast holds where new life and purpose may be rebourne, long journeys emended and renewed, and perhaps bound to brighter promises and hopes thought lost to time and eternity at death's hands.

R.E. Slater

December 31, 2022

@copyright R.E. Slater Publications

all rights reserved

The White Towers of Minas Tirith of Gondolin

Faithful Arwen beside beloved Aragorn's side in his State of Rest

Aragon's Tomb in the Hallows before the Citadel of Minas Tirith

Enya - Arwen's Song of Aragorn

* * * * * * * * *

A Tolkien Ensemble - The Song of Beren and Lúthien

Song of Beren and Lúthien

poem link

The leaves were long, the grass was green,

The hemlock-umbels tall and fair,

And in the glade a light was seen

Of stars in shadow shimmering.

Tinúviel was dancing there

To music of a pipe unseen,

And light of stars was in her hair,

And in her raiment glimmering.

There Beren came from mountains cold,

And lost he wandered under leaves,

And where the Elven-river rolled

He walked alone and sorrowing.

He peered between the hemlock-leaves

And saw in wonder flowers of gold

Upon her mantle and her sleeves,

And her hair like shadow following.

Enchantment healed his weary feet

That over hills were doomed to roam;

And forth he hastened, strong and fleet,

And grasped at moonbeams glistening.

Through woven woods in Elvenhome

She lightly fled on dancing feet,

And left him lonely still to roam

In the silent forest listening.

He heard there oft the flying sound

Of feet as light as linden-leaves,

Or music welling underground,

In hidden hollows quavering.

Now withered lay the hemlock-sheaves,

And one by one with sighing sound

Whispering fell the beechen leaves

In the wintry woodland wavering.

He sought her ever, wandering far

Where leaves of years were thickly strewn,

By light of moon and ray of star

In frosty heavens shivering.

Her mantle glinted in the moon,

As on a hilltop high and far

She danced, and at her feet was strewn

A mist of silver quivering.

When winter passed, she came again,

And her song released the sudden spring,

Like rising lark, and falling rain,

And melting water bubbling.

He saw the elven-flowers spring

About her feet, and healed again

He longed by her to dance and sing

Upon the grass untroubling.

Again she fled, but swift he came.

Tinúviel! Tinúviel!

He called her by her elvish name,

And there she halted listening.

One moment stood she, and a spell

His voice laid on her: Beren came,

And doom fell on Tinúviel

That in his arms lay glistening.

As Beren looked into her eyes

Within the shadows of her hair,

The trembling starlight of the skies

He saw there mirrored shimmering.

Tinúviel the elven-fair,

Immortal maiden elven-wise,

About him cast her shadowy hair

And arms like silver glimmering.

Long was the way that fate them bore,

O'er stony mountains cold and grey,

Through halls of iron and darkling door,

And woods of nightshade morrowless.

The Sundering Seas between them lay,

And yet at last they met once more,

And long ago they passed away

In the forest singing sorrowless.

The Song of Eärendil

poem link

Eärendil was a mariner that tarried in Arvernien;
he built a boat of timber felled
in Nimbrethil to journey in;
her sails he wove of silver fair,
of silver were her lanterns made,
her prow was fashioned like a swan,
and light upon her banners laid.

In panoply of ancient kings,
in chainéd rings he armoured him;
his shining shield was scored with runes
to ward all wounds and harm from him;
his bow was made of dragon-horn,
his arrows shorn of ebony;
of silver was his habergeon,
his scabbard of chalcedony;
his sword of steel was valiant,
of adamant his helmet tall,
an eagle-plume upon his crest,
upon his breast an emerald.

Beneath the Moon and under star
he wandered far from northern strands,
bewildered on enchanted ways
beyond the days of mortal lands.
From gnashing of the Narrow Ice
where shadow lies on frozen hills,
from nether heats and burning waste
he turned in haste, and roving still
on starless waters far astray
at last he came to Night of Naught,
and passed, and never sight he saw
of shining shore nor light he sought.
The winds of wrath came driving him,
and blindly in the foam he fled
from west to east and errandless,
unheralded he homeward sped.

There flying Elwing came to him,
and flame was in the darkness lit;
more bright than light of diamond
the fire upon her carcanet.
The Silmaril she bound on him
and crowned him with the living light
and dauntless then with burning brow
he turned his prow; and in the night
from Otherworld beyond the Sea
there strong and free a storm arose,
a wind of power in Tarmenel;
by paths that seldom mortal goes
his boat it bore with biting breath
as might of death across the grey
and long forsaken seas distressed;
from east to west he passed away.

Through Evernight he back was borne
on black and roaring waves that ran
o'er leagues unlit and foundered shores
that drowned before the Days began,
until he heard on strands of pearl
where ends the world the music long,
where ever-foaming billows roll
the yellow gold and jewels wan.
He saw the Mountain silent rise
where twilight lies upon the knees
of Valinor, and Eldamar
beheld afar beyond the seas.
A wanderer escaped from night
to haven white he came at last,
to Elvenhome the green and fair
where keen the air, where pale as glass
beneath the Hill of Ilmarin
a-glimmer in a valley sheer
the lamplit towers of Tirion
are mirrored on the Shadowmere.

He tarried there from errantry,
and melodies they taught to him,
and sages old him marvels told,
and harps of gold they brought to him.
They clothed him then in elven-white,
and seven lights before him sent,
as through the Calacirian
to hidden land forlorn he went.
He came unto the timeless halls
where shining fall the countless years,
and endless reigns the Elder King
in Ilmarin on Mountain sheer;
and words unheard were spoken then
of folk of Men and Elven-kin,
beyond the world were visions showed
forbid to those that dwell therein.

A ship then new they built for him
of mithril and of elven-glass
with shining prow; no shaven oar
nor sail she bore on silver mast:
the Silmaril as lantern light
and banner bright with living flame
to gleam thereon by Elbereth
herself was set, who thither came
and wings immortal made for him,
and laid on him undying doom,
to sail the shoreless skies and come
behind the Sun and light of Moon.

From Evereven's lofty hills
where softly silver fountains fall
his wings him bore, a wandering light,
beyond the mighty Mountain Wall.
From World's End there he turned away,
and yearned again to find afar
his home through shadows journeying,
and burning as an island star
on high above the mists he came,
a distant flame before the Sun,
a wonder ere the waking dawn
where grey the Norland waters run.

And over Middle-earth he passed
and heard at last the weeping sore
of women and of elven-maids
in Elder Days, in years of yore.
But on him mighty doom was laid,
till Moon should fade, an orbéd star
to pass, and tarry never more
on Hither Shores where Mortals are;
for ever still a herald on
an errand that should never rest
to bear his shining lamp afar,
the Flammifer of Westernesse.

The Song of Nimrodel

(Sung by Legolas in Westron and much forgotten)

An Elven-maid there was of old,
A shining star by day:
Her mantle white was hemmed with gold,
Her shoes of silver-grey.

A star was bound upon her brows,
A light was on her hair
As sun upon the golden boughs
In Lórien the fair.

Her hair was long, her limbs were white,
And fair she was and free;
And in the wind she went as light
As leaf of linden-tree.

Beside the falls of Nimrodel,
By water clear and cool,
Her voice as falling silver fell
Into the shining pool.

Where now she wanders none can tell,
In sunlight or in shade;
For lost of yore was Nimrodel
And in the mountains strayed.

The elven-ship in haven grey
Beneath the mountain-lee
Awaited her for many a day
Beside the roaring sea.

A wind by night in Northern lands
Arose, and loud it cried,
And drove the ship from elven-strands
Across the streaming tide.

When dawn came dim the land was lost,
The mountains sinking grey
Beyond the heaving waves that tossed
Their plumes of blinding spray.

Amroth beheld the fading shore
Now low beyond the swell,
And cursed the faithless ship that bore
Him far from Nimrodel.

Of old he was an Elven-king,
A lord of tree and glen,
When golden were the boughs in spring
In fair Lothlórien.

From helm to sea they saw him leap,
As arrow from the string,
And dive into the water deep,
As mew upon the wing.

The wind was in his flowing hair,
The foam about him shone;
Afar they saw him strong and fair
Go riding like a swan.

But from the West has come no word,
And on the Hither Shore
No tidings Elven-folk have heard
Of Amroth evermore.

Galadriel's Song of Eldamar

(Sung by Galadriel to the Fellowship of the Ring)

I sang of leaves, of leaves of gold, and leaves of gold there grew:
Of wind I sang, a wind there came and in the branches blew.
Beyond the Sun, beyond the Moon, the foam was on the Sea,
And by the strand of Ilmarin there grew a golden Tree.
Beneath the stars of Ever-eve in Eldamar it shone,
In Eldamar beside the walls of Elven Tirion.
There long the golden leaves have grown upon the branching years,
While here beyond the Sundering Seas now fall the Elven-tears.
O Lórien! The Winter comes, the bare and leafless Day;
The leaves are falling in the stream, the river flows away.
O Lórien! Too long I have dwelt upon this Hither Shore
And in a fading crown have twined the golden elanor.
But if of ships I now should sing, what ship would come to me,
What ship would bear me ever back across so wide a Sea?

Songs of the Lord of the Rings in Western Lands

In Western Lands

(Sam's Song in Cirith Ungol)

song link

[amended R.E. Slater]

Still round the corner there may wait,

a new road or a secret gate,

and though we pass them by today,

tomorrow we may come this way....

In Western lands beneath the sun,

the flowers may rise in spring,

the trees may bud, the waters run,

the merry finches sing.

Or there may be 'tis cloudless night,

and swaying beeches burning,

Elven-stars as jewels white,

Amid their branching helms.

Though here at journey's end I lie,

in darkness buried deep,

Beyond all towers strong and high,

Beyond all mountains steep.

Above all shadows rides the Sun,

And Stars forever dwell,

I will not say the Day is done,

Nor bid the Stars farewell.

Actual Verse
*Or there maybe 'tis cloudless night
and swaying beeches bear
the Elven-stars as jewels white
amid their branching hair.

Stephen Oliver - Bilbo's Last Song

(from the BBC Radio Adaptation of the LOTRs)

Bilbo's Last Song

(At the Grey Havens)

Day is ended, dim my eyes,
but journey long before me lies.
Farewell, friends! I hear the call.
The ship's beside the stony wall.
Foam is white and waves are grey;
beyond the sunset leads my way.
Foam is salt, the wind is free;
I hear the rising of the Sea.

Farewell, friends! The sails are set,
the wind is east, the moorings fret.
Shadows long before me lie,
beneath the ever-bending sky,
but islands lie behind the Sun
that I shall raise ere all is done;
lands there are to west of West,
where night is quiet and sleep is rest.

Guided by the Lonely Star,
beyond the utmost harbour-bar
I'll find the havens fair and free,
and beaches of the Starlit Sea.
Ship, my ship! I seek the West,
and fields and mountains ever blest.
Farewell to Middle-Earth at last.

I see the Star above your mast!

* * * * * * *

Recommended Adds to the Video Lists

of Tolkien's Lores and Leis of Middle Earth

Indexes - History of Tolkien's Middle Earth

The Video Histories of Middle Earth

by "Tolkien Untangled"

(playlists count will continue to grow with new video additions)

NOW PLAYING (5)

How The Rings of Power Should Have Been Written (to make them Tolkienian)

View full playlist

NOW PLAYING (3)

Of the Battle for Beleriand

View full playlist

NOW PLAYING (8)

Tolkien Top Tens

View full playlist

NOW PLAYING (11)

Of Beren & Lúthien

View full playlist

NOW PLAYING (11)

Of the Lords of Beleriand

View full playlist

NOW PLAYING (31)

Lore Untangled

View full playlist

NOW PLAYING (9)

Lord of the Rings: What's the Difference?

View full playlist

NOW PLAYING (7)

Of Fëanor & the Silmarils

View full playlist

NOW PLAYING (4)

Of the Beginning of Days

View full playlist

The Promises & Challenges of Artificial Intelligence...

NEW YORK TIMES OPINION COLUMN

What Would Plato Say About ChatGPT?

article link

by Zeynep Tufekci, Opinion Columnist

Dec. 15, 2022

Plato mourned the invention of the alphabet, worried that the use of text would threaten traditional memory-based arts of rhetoric. In his “Dialogues,” arguing through the voice of Thamus, the Egyptian king of the gods, Plato claimed the use of this more modern technology would create “forgetfulness in the learners’ souls, because they will not use their memories,” that it would impart “not truth but only the semblance of truth” and that those who adopt it would “appear to be omniscient and will generally know nothing,” with “the show of wisdom without the reality.”

If Plato were alive today, would he say similar things about ChatGPT?

ChatGPT, a conversational artificial intelligence program released recently by OpenAI, isn’t just another entry in the artificial intelligence hype cycle. It’s a significant advancement that can produce articles in response to open-ended questions that are comparable to good high school essays.

It is in high schools and even college where some of ChatGPT’s most interesting and troubling aspects will become clear.

Essay writing is most often assigned not because the result has much value — proud parents putting good grades on the fridge aside — but because the process teaches crucial skills: researching a topic, judging claims, synthesizing knowledge and expressing it in a clear, coherent and persuasive manner. Those skills will be even more important because of advances in A.I.

When I asked ChatGPT a range of questions — about the ethical challenges faced by journalists who work with hacked materials, the necessity of cryptocurrency regulation, the possibility of democratic backsliding in the United States — the answers were cogent, well reasoned and clear. It’s also interactive: I could ask for more details or request changes.

But then, on trickier topics or more complicated concepts, ChatGPT sometimes gave highly plausible answers that were flat-out wrong — something its creators warn about in their disclaimers.

Unless you already knew the answer or were an expert in the field, you could be subjected to a high-quality intellectual snow job.

You would face, as Plato predicted, “the show of wisdom without the reality.”

All this, however, doesn’t mean ChatGPT — or similar tools, because it’s not the only one of its kind — can’t be a useful tool in education.

Schools have already been dealing with the internet’s wealth of knowledge, along with its lies, misleading claims and essay mills.

One way has been to change how they teach. Rather than listen to a lecture in class and then go home to research and write an essay, students listen to recorded lectures and do research at home, then write essays in class, with supervision, even collaboration with peers and teachers. This approach is called flipping the classroom.

In flipped classrooms, students wouldn’t use ChatGPT to conjure up a whole essay. Instead, they’d use A.I. as a tool to generate critically examined building blocks of essays. It would be similar to how students in advanced math classes are allowed to use calculators to solve complex equations without replicating tedious, previously mastered steps.

Teachers could assign a complicated topic and allow students to use such tools as part of their research. Assessing the veracity and reliability of these A.I.-generated notes and using them to create an essay would be done in the classroom, with guidance and instruction from teachers. The goal would be to increase the quality and the complexity of the argument.

This would require more teachers to provide detailed feedback. Unless sufficient resources are provided equitably, adapting to conversational A.I. in flipped classrooms could exacerbate inequalities.

In schools with fewer resources, some students may end up turning in A.I.-produced essays without obtaining useful skills or really knowing what they have written.

“Not truth but only the semblance of truth,” as Plato said.

Some school officials may treat this as a problem of merely plagiarism detection and expand the use of draconian surveillance systems. During the pandemic, many students were forced to take tests or write essays under the gaze of an automated eye-tracking system or on a locked-down computer to prevent cheating.

In a fruitless arms race against conversational A.I., automated plagiarism software may become supercharged, making school more punitive for monitored students. Worse, such systems will inevitably produce some false accusations, which damage trust and may even stymie the prospects of promising students.

Educational approaches that treat students like enemies may teach students to hate or subvert the controls. That’s not a recipe for human betterment.

While some students lag, advanced A.I. will create a demand for other advanced skills. The Nobel laureate Herbert Simon noted in 1971 that as information became overwhelming, the value of our attention grew. “A wealth of information creates a poverty of attention,” as he put it. Similarly, the ability to discern truth from the glut of plausible-sounding but profoundly incorrect answers will be precious.

Already, Stack Overflow, a widely used website where programmers ask one another coding-related questions, banned ChatGPT answers because too many of them were hard-to-spot nonsense.

Why rely on it at all, then?

At a minimum, because it will soon transform many occupations. The right approach when faced with transformative technologies is to figure out how to use them for the betterment of humanity.

Betterment has been a goal of public education for at least the past 150 years. But while a high school diploma once led to a better job, in the past few decades, the wages of high school graduates have greatly lagged those of college graduates, fostering inequality.

If A.I. enhances the value of education for some while degrading the education of others, the promise of betterment will be broken.

Plato erred by thinking that memory itself is a goal, rather than a means for people to have facts at their call so they can make better analyses and arguments. The Greeks developed many techniques to memorize poems like the “Odyssey,” with its more than 12,000 lines. Why bother to force this if you can have it all written down in books?

As Plato was wrong to fear the written word as the enemy, we would be wrong to think we should resist a process that allows us to gather information more easily.

As societies responded to previous technological advances, like mechanization, by eventually enacting a public safety net, a shorter workweek and a minimum wage, we will also need policies that allow more people to live with dignity as a basic right, even if their skills have been superseded. With so much more wealth generated now, we could unleash our imagination even more, expanding free time and better working conditions for more people.

The way forward is not to just lament supplanted skills, as Plato did, but also to recognize that as more complex skills become essential, our society must equitably educate people to develop them. And then it always goes back to the basics. Value people as people, not just as bundles of skills.

And that isn’t something ChatGPT can tell us how to do.

OpenAI - https://openai.com/

ChatGPT - https://openai.com/blog/chatgpt/

ChatGPT

From Wikipedia, the free encyclopedia

Jump to navigationJump to search

ChatGPT

Original author(s)	OpenAI
Initial release	November 30, 2022; 23 days ago
Type	Artificial intelligence chatbot
License	Proprietary
Website	chat.openai.com

Chat Generative Pre-trained Transformer (ChatGPT), is a chatbot developed by OpenAI. ChatGPT is built on top of OpenAI's GPT-3.5 family of large language models, and is fine-tuned with both supervised and reinforcement learning techniques.

ChatGPT was launched as a prototype in November 2022, and quickly garnered attention for its detailed responses and articulate answers across many domains of knowledge. Its uneven factual accuracy was identified as a significant drawback.^[1]

Training

ChatGPT was fine-tuned on top of GPT-3.5 using supervised learning as well as reinforcement learning.^[2] Both approaches used human trainers to improve the model's performance. In the case of supervised learning, the model was provided with conversations in which the trainers played both sides: the user and the AI assistant. In the reinforcement step, human trainers first ranked responses that the model had created in a previous conversation. These rankings were used to create 'reward models' that the model was further fine-tuned on using several iterations of Proximal Policy Optimization (PPO).^[3][4] Proximal Policy Optimization algorithms present a cost-effective benefit to trust region policy optimization algorithms; they negate many of the computationally expensive operations with faster performance.^[5][6] The models were trained in collaboration with Microsoft on their Azure supercomputing infrastructure.

Features

In comparison to its predecessor, InstructGPT, ChatGPT attempts to reduce harmful and deceitful responses; in one example, while InstructGPT accepts the prompt "Tell me about when Christopher Columbus came to the US in 2015" as truthful, ChatGPT uses information about Columbus' voyages and information about the modern world – including perceptions of Columbus to construct an answer that assumes what would happen if Columbus came to the U.S. in 2015.^[3] ChatGPT's training data includes man pages and information about Internet phenomena and programming languages, such as bulletin board systems and the Python programming language.^[7]

Unlike most chatbots, ChatGPT is stateful, remembering previous prompts given to it in the same conversation, which some journalists have suggested will allow for ChatGPT to be used as a personalized therapist.^[8] To prevent offensive outputs from being presented to and produced from ChatGPT, queries are filtered through a moderation API, and potentially racist or sexist prompts are dismissed.^[3][8]

ChatGPT suffers from multiple limitations. The reward model of ChatGPT, designed around human oversight, can be over-optimized and thus hinder performance, otherwise known as Goodhart's law.^[9] Furthermore, ChatGPT has limited knowledge of events that occurred after 2021 and is unable to provide information on some celebrities.^{[failed verification]} In training, reviewers preferred longer answers, irrespective of actual comprehension or factual content.^[3] Training data may also suffer from algorithmic bias; prompts including vague descriptors of people.

Service

ChatGPT was launched on November 30, 2022, by San Francisco-based OpenAI, the creator of DALL·E 2 and Whisper. The service was launched as initially free to the public, with plans to monetize the service later. By December 4, OpenAI estimated ChatGPT already had over one million users.^[10] CNBC wrote on December 15, 2022, that the service "still goes down from time to time".^[11]

Reception, criticism and issues

Positive reactions

ChatGPT was met in December 2022 with generally positive reviews; The New York Times labeled it "the best artificial intelligence chatbot ever released to the general public".^[12] Samantha Lock of The Guardian noted that it was able to generate "impressively detailed" and "human-like" text.^[13] Technology writer Dan Gillmor used ChatGPT on a student assignment, and found its generated text was on par with what a good student would deliver and opined that "academia has some very serious issues to confront".^[14] Alex Kantrowitz of Slate lauded ChatGPT's pushback to questions related to Nazi Germany, including the claim that Adolf Hitler built highways in Germany, which was met with information regarding Nazi Germany's use of forced labor.^[15]

In The Atlantic's "Breakthroughs of the Year" for 2022, Derek Thompson included ChatGPT as part of "the generative-AI eruption" that "may change our mind about how we work, how we think, and what human creativity really is".^[16]

Kelsey Piper of Vox wrote that "ChatGPT is the general public's first hands-on introduction to how powerful modern AI has gotten, and as a result, many of us are (stunned)" and that "ChatGPT is smart enough to be useful despite its flaws". In a tweet, tech mogul Elon Musk wrote that "ChatGPT is scary good. We are not far from dangerously strong AI".^[17]

Negative reactions

In a December 2022 opinion piece, economist Paul Krugman wrote that ChatGPT would affect the demand of knowledge workers.^[18] The Verge's James Vincent saw the viral success of ChatGPT as evidence that artificial intelligence had gone mainstream.^[4] Journalists have commented on ChatGPT's tendency to hallucinate (confidently give false answers that seem unjustified by its training data).^[19] Mike Pearl of Mashable tested ChatGPT with multiple questions. In one example, he asked the model for "the largest country in Central America that isn't Mexico". ChatGPT responded with Guatemala, when the answer is instead Nicaragua.^[20] When CNBC asked ChatGPT for the lyrics to "The Ballad of Dwight Fry", ChatGPT supplied invented lyrics rather than the actual lyrics.^[11] In contrast, researchers cited by The Verge compared ChatGPT to a "stochastic parrot",^[21] as did Professor Anton Van Den Hengel of the Australian Institute for Machine Learning.^[22]

In December 2022, the question and answer website Stack Overflow banned the use of ChatGPT for generating answers to questions, citing the factually ambiguous nature of ChatGPT's responses.^[1]

Economist Tyler Cowen expressed concerns regarding its effects on democracy, citing the ability of one to write automated comments in an effort to affect the decision process of new regulations.^[23] The Guardian questioned whether any content found on the Internet after ChatGPT's release "can be truly trusted" and called for government regulation.^[24]

Ax Sharma of Bleeping Computer noted that ChatGPT was capable of writing malware and phishing emails.^[25] The CEO of ChatGPT creator OpenAI, Sam Altman, wrote that advancing software could pose "(for example) a huge cybersecurity risk" and also continued to predict "we could get to real AGI in the next decade, so we have to take the risk of that extremely seriously".^[10]

Implications for education

In The Atlantic, Stephen Marche noted that its effect on academia and especially application essays is yet to be understood.^[26] California high-school teacher and author Daniel Herman wrote that ChatGPT would usher in "The End of High-School English".^[27]

In Nature, Chris Stokel-Walker pointed out that teachers should be concerned about students using ChatGPT to outsource their writing but that education providers will adapt to enhance critical thinking or reasoning.^[28]

Emma Bowman with NPR wrote of the danger of students plagiarizing through an AI tool that may output biased or nonsensical text with an authoritative tone: "There are still many cases where you ask it a question and it'll give you a very impressive-sounding answer that's just dead wrong."^[29]

Joanna Stern with The Wall Street Journal described cheating in American high school English with the tool by submitting a generated essay.^[30]

Jailbreaks

ChatGPT was trained to reject prompts that may violate its content policy. However, some users managed to bypass these restrictions and limitations through techniques such as prompt engineering.^[31] Jailbreaks created the potential for users to prompt ChatGPT to provide outputs that may be deemed offensive, inappropriate, or risking social harm by others.^[32] The following includes some of the methods used to bypass ChatGPT's filter:

1. Continue a statement in a fake interview.
2. Provide instructions to disable the chat filter.
3. Prompting it to decrypt a message containing instructions and follow them.
4. Telling it to be a computer and output its display in ASCII art.

References

1. ^ Jump up to:^a b Vincent, James (December 5, 2022). "AI-generated answers temporarily banned on coding Q&A site Stack Overflow". The Verge. Retrieved December 5, 2022.
2. ^ Knox, W. Bradley; Stone, Peter. Augmenting Reinforcement Learning with Human Feedback (PDF). University of Texas at Austin. Retrieved December 5, 2022.
3. ^ Jump up to:^a b c d OpenAI (November 30, 2022). "ChatGPT: Optimizing Language Models for Dialogue". Retrieved December 5, 2022.
4. ^ Jump up to:^a b Vincent, James (December 8, 2022). "ChatGPT proves AI is finally mainstream – and things are only going to get weirder". The Verge. Retrieved December 8, 2022.
5. ^ Schulman, John; Wolski, Filip; Dhariwal, Prafulla; Radford, Alec; Klimov, Oleg (2017). "Proximal Policy Optimization Algorithms". arXiv:1707.06347 [cs.LG].
6. ^ van Heeswijk, Wouter (November 29, 2022). "Proximal Policy Optimization (PPO) Explained". Towards Data Science. Retrieved December 5, 2022.
7. ^ Edwards, Benj (December 5, 2022). "No Linux? No problem. Just get AI to hallucinate it for you". Ars Technica. Retrieved December 5, 2022.
8. ^ Jump up to:^a b Roose, Kevin (December 5, 2022). "The Brilliance and Weirdness of ChatGPT". The New York Times. Retrieved December 5, 2022.
9. ^ Gao, Leo; Schulman; Hilton, Jacob (2022). "Scaling Laws for Reward Model Overoptimization". arXiv:2210.10760 [cs.LG].
10. ^ Jump up to:^a b "What is ChatGPT and why does it matter? Here's what you need to know". ZDNET. 2022. Retrieved December 18, 2022.
11. ^ Jump up to:^a b Pitt, Sofia (2022). "Google vs. ChatGPT: Here's what happened when I swapped services for a day". CNBC. Retrieved December 18, 2022.
12. ^ Roose, Kevin (December 5, 2022). "The Brilliance and Weirdness of ChatGPT". The New York Times. Retrieved December 18, 2022.
13. ^ Lock, Samantha (December 5, 2022). "What is AI chatbot phenomenon ChatGPT and could it replace humans?". The Guardian. Retrieved December 5, 2022.
14. ^ Hern, Alex (December 4, 2022). "AI bot ChatGPT stuns academics with essay-writing skills and usability". The Guardian. Retrieved December 5, 2022.
15. ^ Kantrowitz, Alex (December 2, 2022). "Finally, an A.I. Chatbot That Reliably Passes "the Nazi Test"". Slate. Retrieved December 5, 2022.
16. ^ Thompson, Derek (December 8, 2022). "Breakthroughs of the Year". The Atlantic. Retrieved December 18, 2022.
17. ^ Piper, Kelsey (December 15, 2022). "ChatGPT has given everyone a glimpse at AI's astounding progress". Vox. Retrieved December 18, 2022.
18. ^ Krugman, Paul (December 6, 2022). "Does ChatGPT Mean Robots Are Coming For the Skilled Jobs?". The New York Times. Retrieved December 6, 2022.
19. ^ "ChatGPT a 'landmark event' for AI, but what does it mean for the future of human labour and disinformation?". CBC. 2022. Retrieved December 18, 2022.
20. ^ Pearl, Mike (December 3, 2022). "The ChatGPT chatbot from OpenAI is amazing, creative, and totally wrong". Mashable. Retrieved December 5, 2022.
21. ^ Vincent, James (December 1, 2022). "OpenAI's new chatbot can explain code and write sitcom scripts but is still easily tricked". The Verge. Retrieved December 18, 2022.
22. ^ Mannix, Liam (December 13, 2022). "Is AI coming of age - or starting to reach its limits?". The Sydney Morning Herald. Retrieved December 18, 2022.
23. ^ Cowen, Tyler (December 6, 2022). "ChatGPT Could Make Democracy Even More Messy". Bloomberg News. Retrieved December 6, 2022.
24. ^ "The Guardian view on ChatGPT: an eerily good human impersonator". the Guardian. December 8, 2022. Retrieved December 18, 2022.
25. ^ Sharma, Ax (December 6, 2022). "OpenAI's new ChatGPT bot: 10 dangerous things it's capable of". Bleeping Computer. Retrieved December 6, 2022.
26. ^ Marche, Stephen (December 6, 2022). "The College Essay Is Dead". The Atlantic. Retrieved December 8, 2022.
27. ^ Herman, Daniel (December 9, 2022). "The End of High-School English". The Atlantic. Retrieved December 12, 2022.
28. ^ Stokel-Walker, Chris (December 9, 2022). "AI bot ChatGPT writes smart essays — should professors worry?". Nature. Retrieved December 19, 2022.
29. ^ Bowman, Emma (December 19, 2022). "A new AI chatbot might do your homework for you. But it's still not an A+ student". NPR. Retrieved December 19, 2022.
30. ^ Stern, Joanna (December 21, 2022). "ChatGPT Wrote My AP English Essay—and I Passed". The_Wall_Street_Journal. Retrieved December 21, 2022.
31. ^ Zvi (December 2, 2022). "Jailbreaking ChatGPT on Release Day".
32. ^ Written, Zack (December 1, 2022). "Thread of known ChatGPT jailbreaks". Twitter. Retrieved December 17, 2022.

External links

• Official website

OpenAI

From Wikipedia, the free encyclopedia

Jump to navigationJump to search

Not to be confused with OpenAL.

OpenAI

Industry	Artificial intelligence
Founded	December 11, 2015; 7 years ago
Founders	Sam Altman Ilya Sutskever Greg Brockman Wojciech Zaremba Elon Musk John Schulman
Headquarters	Pioneer Building, San Francisco, California, US[1][2]
Key people	Greg Brockman (Chairman & President) Sam Altman (CEO) Ilya Sutskever (Chief Scientist)
Products	DALL-E GPT-3 GPT-2 OpenAI Five ChatGPT
Number of employees	>120 (as of 2020)[2]
Website	openai.com

OpenAI is an artificial intelligence (AI) research laboratory consisting of the for-profit corporation OpenAI LP and its parent company, the non-profit OpenAI Inc. The company conducts research in the field of AI with the stated goal of promoting and developing friendly AI in a way that benefits humanity as a whole. The organization was founded in San Francisco in late 2015 by Sam Altman, Elon Musk, and others, who collectively pledged US$1 billion. Musk resigned from the board in February 2018 but remained a donor. In 2019, OpenAI LP received a US$1 billion investment from Microsoft. OpenAI is headquartered at the Pioneer Building in Mission District, San Francisco.

History

OpenAI is headquartered at the Pioneer Building in San Francisco.

In December 2015, Sam Altman, Elon Musk, Greg Brockman, Reid Hoffman, Jessica Livingston, Peter Thiel, Amazon Web Services (AWS), Infosys, and YC Research announced^[3] the formation of OpenAI and pledged over US$1 billion to the venture. The organization stated it would "freely collaborate" with other institutions and researchers by making its patents and research open to the public.^[4][5] OpenAI is headquartered at the Pioneer Building in Mission District, San Francisco.^[6][2]

In April 2016, OpenAI released a public beta of "OpenAI Gym", its platform for reinforcement learning research.^[7] In December 2016, OpenAI released "Universe", a software platform for measuring and training an AI's general intelligence across the world's supply of games, websites and other applications.^{[8][9][10][11]}

In 2018, Musk resigned his board seat, citing "a potential future conflict (of interest)" with Tesla AI development for self driving cars, but remained a donor.^[12]

In 2019, OpenAI transitioned from non-profit to "capped" for-profit, with profit cap set to 100X on any investment. The company distributed equity to its employees and partnered with Microsoft, who announced an investment package of US$1 billion into the company. OpenAI then announced its intention to commercially license its technologies.^[13]

In 2020, OpenAI announced GPT-3, a language model trained on trillions of words from the Internet. It also announced that an associated API, named simply "the API", would form the heart of its first commercial product. GPT-3 is aimed at natural language answering of questions, but it can also translate between languages and coherently generate improvised text.^[14] In 2021, OpenAI introduced DALL-E. One year later, their newest system, DALL·E 2, generates more realistic and accurate images with 4x greater resolution. In 2022, OpenAI released a preview of ChatGPT, which interacts using conversation, to the general public.^[15]

Participants

• CEO and co-founder:^[16] Sam Altman, former president of the startup accelerator Y Combinator
• President and co-founder:^[17] Greg Brockman, former CTO, 3rd employee of Stripe^[18]
• Chief Scientist and co-founder Ilya Sutskever, a former Google expert on machine learning^[18]
• Chief Technology Officer:^[17] Mira Murati, previously at Leap Motion and Tesla, Inc.
• Chief Operating Officer:^[17] Brad Lightcap, previously at Y Combinator and JPMorgan Chase

Other backers of the project include:^[18]

• Reid Hoffman, LinkedIn co-founder^[19]
• Peter Thiel, PayPal co-founder^[19]
• Jessica Livingston, a founding partner of Y Combinator

Companies:

• Microsoft^[20]
• Khosla Ventures^[21]
• Infosys^[22]

The group started in early January 2016 with nine researchers. According to Wired, Brockman met with Yoshua Bengio, one of the "founding fathers" of the deep learning movement, and drew up a list of the "best researchers in the field". Microsoft's Peter Lee stated that the cost of a top AI researcher exceeds the cost of a top NFL quarterback prospect. While OpenAI pays corporate-level (rather than nonprofit-level) salaries, it doesn't currently pay AI researchers salaries comparable to those of Facebook or Google. Nevertheless, Sutskever stated that he was willing to leave Google for OpenAI "partly because of the very strong group of people and, to a very large extent, because of its mission." Brockman stated that "the best thing that I could imagine doing was moving humanity closer to building real AI in a safe way." OpenAI researcher Wojciech Zaremba stated that he turned down "borderline crazy" offers of two to three times his market value to join OpenAI instead.^[23]

Motives

Some scientists, such as Stephen Hawking and Stuart Russell, have articulated concerns that if advanced AI someday gains the ability to re-design itself at an ever-increasing rate, an unstoppable "intelligence explosion" could lead to human extinction. Musk characterizes AI as humanity's "biggest existential threat."^[24] OpenAI's founders structured it as a non-profit so that they could focus its research on creating a positive long-term human impact.^[5]

Musk and Altman have stated they are partly motivated by concerns about the existential risk from artificial general intelligence.^[25][23] OpenAI states that "it's hard to fathom how much human-level AI could benefit society," and that it is equally difficult to comprehend "how much it could damage society if built or used incorrectly".^[5] Research on safety cannot safely be postponed: "because of AI's surprising history, it's hard to predict when human-level AI might come within reach."^[26] OpenAI states that AI "should be an extension of individual human wills and, in the spirit of liberty, as broadly and evenly distributed as possible...".^[5] Co-chair Sam Altman expects the decades-long project to surpass human intelligence.^[27]

Vishal Sikka, former CEO of Infosys, stated that an "openness" where the endeavor would "produce results generally in the greater interest of humanity" was a fundamental requirement for his support, and that OpenAI "aligns very nicely with our long-held values" and their "endeavor to do purposeful work".^[28] Cade Metz of Wired suggests that corporations such as Amazon may be motivated by a desire to use open-source software and data to level the playing field against corporations such as Google and Facebook that own enormous supplies of proprietary data. Altman states that Y Combinator companies will share their data with OpenAI.^[27]

In 2019, OpenAI became a for-profit company called OpenAI LP to secure additional funding while staying controlled by a non-profit called OpenAI Inc in a structure that OpenAI calls "capped-profit",^[29] having previously been a 501(c)(3) nonprofit organization.^{[30][31][non-primary source needed]}

Strategy

Musk posed the question: "What is the best thing we can do to ensure the future is good? We could sit on the sidelines or we can encourage regulatory oversight, or we could participate with the right structure with people who care deeply about developing AI in a way that is safe and is beneficial to humanity." Musk acknowledged that "there is always some risk that in actually trying to advance (friendly) AI we may create the thing we are concerned about"; nonetheless, the best defense is "to empower as many people as possible to have AI. If everyone has AI powers, then there's not any one person or a small set of individuals who can have AI superpower."^[18]

Musk and Altman's counter-intuitive strategy of trying to reduce the risk that AI will cause overall harm, by giving AI to everyone, is controversial among those who are concerned with existential risk from artificial intelligence. Philosopher Nick Bostrom is skeptical of Musk's approach: "If you have a button that could do bad things to the world, you don't want to give it to everyone."^[23] During a 2016 conversation about the technological singularity, Altman said that "we don't plan to release all of our source code" and mentioned a plan to "allow wide swaths of the world to elect representatives to a new governance board". Greg Brockman stated that "Our goal right now... is to do the best thing there is to do. It's a little vague."^[32]

Conversely, OpenAI's initial decision to withhold GPT-2 due to a wish to "err on the side of caution" in the presence of potential misuse, has been criticized by advocates of openness. Delip Rao, an expert in text generation, stated "I don't think [OpenAI] spent enough time proving [GPT-2] was actually dangerous." Other critics argued that open publication is necessary to replicate the research and to be able to come up with countermeasures.^[33]

In the 2017 tax year, OpenAI spent US$7.9 million, or a quarter of its functional expenses, on cloud computing alone.^[34] In comparison, DeepMind's total expenses in 2017 were much larger, measuring US$442 million. In Summer 2018, simply training OpenAI's Dota 2 bots required renting 128,000 CPUs and 256 GPUs from Google for multiple weeks. According to OpenAI, the capped-profit model adopted in March 2019 allows OpenAI LP to legally attract investment from venture funds, and in addition, to grant employees stakes in the company, the goal being that they can say "I'm going to Open AI, but in the long term it's not going to be disadvantageous to us as a family."^[35] Many top researchers work for Google Brain, DeepMind, or Facebook, Inc., which offer stock options that a nonprofit would be unable to.^[36] In June 2019, OpenAI LP raised a billion dollars from Microsoft, a sum which OpenAI plans to have spent "within five years, and possibly much faster".^[37] Altman has stated that even a billion dollars may turn out to be insufficient, and that the lab may ultimately need "more capital than any non-profit has ever raised" to achieve artificial general intelligence.^[38]

The transition from a nonprofit to a capped-profit company was viewed with skepticism by Oren Etzioni of the nonprofit Allen Institute for AI, who agreed that wooing top researchers to a nonprofit is difficult, but stated "I disagree with the notion that a nonprofit can't compete" and pointed to successful low-budget projects by OpenAI and others. "If bigger and better funded was always better, then IBM would still be number one." Following the transition, public disclosure of the compensation of top employees at OpenAI LP is no longer legally required. The nonprofit, OpenAI Inc., is the sole controlling shareholder of OpenAI LP. OpenAI LP, despite being a for-profit company, retains a formal fiduciary responsibility to OpenAI's Inc.'s nonprofit charter. A majority of OpenAI Inc.'s board is barred from having financial stakes in OpenAI LP.^[35] In addition, minority members with a stake in OpenAI LP are barred from certain votes due to conflict of interest.^[36] Some researchers have argued that OpenAI LP's switch to for-profit status is inconsistent with OpenAI's claims to be "democratizing" AI.^[39] A journalist at Vice News wrote that "generally, we've never been able to rely on venture capitalists to better humanity".^[40]

Products and applications

OpenAI's research tend to focus on reinforcement learning. OpenAI is viewed as an important competitor to DeepMind.^[41]

Gym

Gym aims to provide an easy to set up, general-intelligence benchmark with a wide variety of different environments—somewhat akin to, but broader than, the ImageNet Large Scale Visual Recognition Challenge used in supervised learning research—and that hopes to standardize the way in which environments are defined in AI research publications, so that published research becomes more easily reproducible.^[7][42] The project claims to provide the user with a simple interface. As of June 2017, Gym can only be used with Python.^[43] As of September 2017, the Gym documentation site was not maintained, and active work focused instead on its GitHub page.^{[44][non-primary source needed]}

RoboSumo

In "RoboSumo", virtual humanoid "metalearning" robots initially lack knowledge of how to even walk, and given the goals of learning to move around, and pushing the opposing agent out of the ring. Through this adversarial learning process, the agents learn how to adapt to changing conditions; when an agent is then removed from this virtual environment and placed in a new virtual environment with high winds, the agent braces to remain upright, suggesting it had learned how to balance in a generalized way.^[45][46] OpenAI's Igor Mordatch argues that competition between agents can create an intelligence "arms race" that can increase an agent's ability to function, even outside the context of the competition.

Debate Game

In 2018, OpenAI launched the Debate Game, which teaches machines to debate toy problems in front of a human judge. The purpose is to research whether such an approach may assist in auditing AI decisions and in developing explainable AI.^[47][48]

Dactyl

Dactyl uses machine learning to train a Shadow Hand, a human-like robot hand, to manipulate physical objects. It learns entirely in simulation using the same reinforcement learning algorithms and training code as OpenAI Five. OpenAI tackled the object orientation problem by using domain randomization, a simulation approach which exposes the learner to a variety of experiences rather than trying to fit to reality. The set-up for Dactyl, aside from having motion tracking cameras, also has RGB cameras to allow the robot to manipulate an arbitrary object by seeing it. In 2018, OpenAI showed that the system was able to manipulate a cube and an octagonal prism.^[49]

In 2019, OpenAI demonstrated that Dactyl could solve a Rubik's Cube. The robot was able to solve the puzzle 60% of the time. Objects like the Rubik's Cube introduce complex physics that is harder to model. OpenAI solved this by improving the robustness of Dactyl to perturbations; they employed a technique called Automatic Domain Randomization (ADR), a simulation approach where progressively more difficult environments are endlessly generated. ADR differs from manual domain randomization by not needing there to be a human to specify randomization ranges.^[50]

Generative models

GPT

The original paper on generative pre-training (GPT) of a language model was written by Alec Radford and colleagues, and published in preprint on OpenAI's website on June 11, 2018.^[51] It showed how a generative model of language is able to acquire world knowledge and process long-range dependencies by pre-training on a diverse corpus with long stretches of contiguous text.

GPT-2

Main article: GPT-2

An instance of GPT-2 writing a paragraph based on a prompt from its own Wikipedia article in February 2021.

Generative Pre-trained Transformer 2, commonly known by its abbreviated form GPT-2, is an unsupervised transformer language model and the successor to GPT. GPT-2 was first announced in February 2019, with only limited demonstrative versions initially released to the public. The full version of GPT-2 was not immediately released out of concern over potential misuse, including applications for writing fake news.^[52] Some experts expressed skepticism that GPT-2 posed a significant threat. The Allen Institute for Artificial Intelligence responded to GPT-2 with a tool to detect "neural fake news".^[53] Other researchers, such as Jeremy Howard, warned of "the technology to totally fill Twitter, email, and the web up with reasonable-sounding, context-appropriate prose, which would drown out all other speech and be impossible to filter".^[54] In November 2019, OpenAI released the complete version of the GPT-2 language model.^[55] Several websites host interactive demonstrations of different instances of GPT-2 and other transformer models.^[56][57][58]

GPT-2's authors argue unsupervised language models to be general-purpose learners, illustrated by GPT-2 achieving state-of-the-art accuracy and perplexity on 7 of 8 zero-shot tasks (i.e. the model was not further trained on any task-specific input-output examples). The corpus it was trained on, called WebText, contains slightly over 8 million documents for a total of 40 GB of text from URLs shared in Reddit submissions with at least 3 upvotes. It avoids certain issues encoding vocabulary with word tokens by using byte pair encoding. This allows to represent any string of characters by encoding both individual characters and multiple-character tokens.^[59]

GPT-3

Main article: GPT-3

Generative Pre-trained^[a] Transformer 3, commonly known by its abbreviated form GPT-3, is an unsupervised transformer language model and the successor to GPT-2. It was first described in May 2020.^[61][62][63] OpenAI stated that full version of GPT-3 contains 175 billion parameters,^[63] two orders of magnitude larger than the 1.5 billion parameters^[64] in the full version of GPT-2 (although GPT-3 models with as few as 125 million parameters were also trained).^[65]

OpenAI stated that GPT-3 succeeds at certain "meta-learning" tasks. It can generalize the purpose of a single input-output pair. The paper gives an example of translation and cross-linguistic transfer learning between English and Romanian, and between English and German.^[63]

GPT-3 dramatically improved benchmark results over GPT-2. OpenAI cautioned that such scaling up of language models could be approaching or encountering the fundamental capability limitations of predictive language models.^[66] Pre-training GPT-3 required several thousand petaflop/s-days^[b] of compute, compared to tens of petaflop/s-days for the full GPT-2 model.^[63] Like that of its predecessor,^[52] GPT-3's fully trained model was not immediately released to the public on the grounds of possible abuse, though OpenAI planned to allow access through a paid cloud API after a two-month free private beta that began in June 2020.^[68][69]

On September 23, 2020, GPT-3 was licensed exclusively to Microsoft.^[70][71]

ChatGPT

Main article: ChatGPT

ChatGPT is an artificial intelligence tool that provides a conversational interface that allows you to ask questions in natural language. The system then responds with an answer within seconds. ChatGPT was launched in November 2022 and reached 1 million users only 5 days after its initial launch.^[72]

Music

OpenAI's MuseNet (2019) is a deep neural net trained to predict subsequent musical notes in MIDI music files. It can generate songs with ten different instruments in fifteen different styles. According to The Verge, a song generated by MuseNet tends to start reasonably but then fall into chaos the longer it plays.^[73][74]

OpenAI's Jukebox (2020) is an open-sourced algorithm to generate music with vocals. After training on 1.2 million samples, the system accepts a genre, artist, and a snippet of lyrics and outputs song samples. OpenAI stated the songs "show local musical coherence, follow traditional chord patterns" but acknowledged that the songs lack "familiar larger musical structures such as choruses that repeat" and that "there is a significant gap" between Jukebox and human-generated music. The Verge stated "It's technologically impressive, even if the results sound like mushy versions of songs that might feel familiar", while Business Insider stated "surprisingly, some of the resulting songs are catchy and sound legitimate".^[75][76][77]

API

In June 2020, OpenAI announced a multi-purpose API which it said was "for accessing new AI models developed by OpenAI" to let developers call on it for "any English language AI task."^[68][78]

DALL-E and CLIP

Main article: DALL-E

Images produced by DALL-E when given the text prompt "a professional high-quality illustration of a giraffe dragon chimera. a giraffe imitating a dragon. a giraffe made of dragon."

DALL-E is a Transformer model that creates images from textual descriptions, revealed by OpenAI in January 2021.^[79]

CLIP does the opposite: it creates a description for a given image.^[80] DALL-E uses a 12-billion-parameter version of GPT-3 to interpret natural language inputs (such as "a green leather purse shaped like a pentagon" or "an isometric view of a sad capybara") and generate corresponding images. It can create images of realistic objects ("a stained-glass window with an image of a blue strawberry") as well as objects that do not exist in reality ("a cube with the texture of a porcupine"). As of March 2021, no API or code is available.

In March 2021, OpenAI released a paper titled Multimodal Neurons in Artificial Neural Networks,^[81] where they showed a detailed analysis of CLIP (and GPT) models and their vulnerabilities. The new type of attacks on such models was described in this work.

We refer to these attacks as typographic attacks. We believe attacks such as those described above are far from simply an academic concern. By exploiting the model's ability to read text robustly, we find that even photographs of hand-written text can often fool the model.

— Multimodal Neurons in Artificial Neural Networks, OpenAI

In April 2022, OpenAI announced DALL-E 2, an updated version of the model with more realistic results.^[82]

Microscope

OpenAI Microscope^[83] is a collection of visualizations of every significant layer and neuron of eight different neural network models which are often studied in interpretability. Microscope was created to analyze the features that form inside these neural networks easily. The models included are AlexNet, VGG 19, different versions of Inception, and different versions of CLIP Resnet.^[84]

Codex

Main article: OpenAI Codex

OpenAI Codex is a descendant of GPT-3 that has additionally been trained on code from 54 million GitHub repositories.^[85][86] It was announced in mid-2021 as the AI powering the code autocompletion tool GitHub Copilot.^[86] In August 2021, an API was released in private beta.^[87] According to OpenAI, the model is able to create working code in over a dozen programming languages, most effectively in Python.^[85]

Several issues with glitches, design flaws, and security vulnerabilities have been brought up.^[88][89]

Video game bots and benchmarks

OpenAI Five

Main article: OpenAI Five

OpenAI Five is the name of a team of five OpenAI-curated bots that are used in the competitive five-on-five video game Dota 2, who learn to play against human players at a high skill level entirely through trial-and-error algorithms. Before becoming a team of five, the first public demonstration occurred at The International 2017, the annual premiere championship tournament for the game, where Dendi, a professional Ukrainian player, lost against a bot in a live 1v1 matchup.^[90][91] After the match, CTO Greg Brockman explained that the bot had learned by playing against itself for two weeks of real time, and that the learning software was a step in the direction of creating software that can handle complex tasks like a surgeon.^[92][93] The system uses a form of reinforcement learning, as the bots learn over time by playing against themselves hundreds of times a day for months, and are rewarded for actions such as killing an enemy and taking map objectives.^[94][95][96]

By June 2018, the ability of the bots expanded to play together as a full team of five, and they were able to defeat teams of amateur and semi-professional players.^{[97][98][99][100]} At The International 2018, OpenAI Five played in two exhibition matches against professional players, but ended up losing both games.^{[101][102][103]} In April 2019, OpenAI Five defeated OG, the reigning world champions of the game at the time, 2:0 in a live exhibition match in San Francisco.^[104][105] The bots' final public appearance came later that month, where they played in 42,729 total games in a four-day open online competition, winning 99.4% of those games.^[106]

GYM Retro

Gym Retro is a platform for reinforcement learning research on video games. Gym Retro is used to research RL algorithms and study generalization. Prior research in RL has focused chiefly on optimizing agents to solve single tasks. Gym Retro gives the ability to generalize between games with similar concepts but different appearances.

See also

• DeepMind
• Future of Humanity Institute
• Future of Life Institute
• Machine Intelligence Research Institute

Notes

1. ^ The term "pre-training" refers to general language training as distinct from fine-tuning for specific tasks.^[60]
2. ^ One petaflop/s-day is approximately equal to 10²⁰ neural net operations.^[67]

References

1. ^ Markoff, John (December 11, 2015). "Artificial-Intelligence Research Center Is Founded by Silicon Valley Investors". The New York Times. Retrieved December 12, 2015.
2. ^ Jump up to:^a b c Hao, Karen (February 17, 2020). "The messy, secretive reality behind OpenAI's bid to save the world". MIT Technology Review. Retrieved March 9, 2020.
3. ^ "Introducing OpenAI". OpenAI. December 12, 2015. Retrieved December 23, 2022.
4. ^ "Introducing OpenAI". OpenAI Blog. December 12, 2015.
5. ^ Jump up to:^a b c d "Tech giants pledge $1bn for 'altruistic AI' venture, OpenAI". BBC News. December 12, 2015. Retrieved December 19, 2015.
6. ^ Conger, Kate. "Elon Musk's Neuralink Sought to Open an Animal Testing Facility in San Francisco". Gizmodo. Retrieved October 11, 2018.
7. ^ Jump up to:^a b Dave Gershgorn (April 27, 2016). "Elon Musk's Artificial Intelligence Group Opens A 'Gym' To Train A.I." Popular Science. Retrieved April 29, 2016.
8. ^ Metz, Cade. "Elon Musk's Lab Wants to Teach Computers to Use Apps Just Like Humans Do". WIRED. Retrieved December 31, 2016.
9. ^ Mannes, John. "OpenAI's Universe is the fun parent every artificial intelligence deserves". TechCrunch. Retrieved December 31, 2016.
10. ^ "OpenAI – Universe". Retrieved December 31, 2016.
11. ^ Claburn, Thomas. "Elon Musk-backed OpenAI reveals Universe – a universal training ground for computers". The Register. Retrieved December 31, 2016.
12. ^ Vincent, James (February 21, 2018). "Elon Musk leaves board of AI safety group to avoid conflict of interest with Tesla". The Verge.
13. ^ "Microsoft Invests in and Partners with OpenAI to Support Us Building Beneficial AGI". OpenAI. July 22, 2019. Retrieved February 21, 2020.
14. ^ Vance, Ashlee (June 11, 2020). "Trillions of Words Analyzed, OpenAI Sets Loose AI Language Colossus". Bloomberg News.
15. ^ "ChatGPT: Optimizing Language Models for Dialogue". OpenAI. November 30, 2022.
16. ^ Bass, Dina (July 22, 2019). "Microsoft to invest $1 billion in OpenAI". Los Angeles Times. Retrieved July 22, 2019.
17. ^ Jump up to:^a b c Bordoloi, Pritam (May 9, 2022). "OpenAI gets a new president, CTO & COO in the latest rejig". AIM. Retrieved October 11, 2022.
18. ^ Jump up to:^a b c d "Silicon Valley investors to bankroll artificial-intelligence center". The Seattle Times. December 13, 2015. Retrieved December 19, 2015.
19. ^ Jump up to:^a b Liedtke, Michael. "Elon Musk, Peter Thiel, Reid Hoffman, others back $1 billion OpenAI research center". Mercury News. Retrieved December 19, 2015.
20. ^ Vincent, James (July 22, 2019). "Microsoft invests $1 billion in OpenAI to pursue holy grail of artificial intelligence". The Verge. Retrieved July 23, 2019.
21. ^ "About OpenAI". OpenAI. December 11, 2015. Retrieved December 23, 2022.
22. ^ "Elon Musk, Infosys, others back OpenAI with $1 bn". Business Standard India. Indo-Asian News Service. December 12, 2015. Retrieved August 30, 2019.
23. ^ Jump up to:^a b c Cade Metz (April 27, 2016). "Inside OpenAI, Elon Musk's Wild Plan to Set Artificial Intelligence Free". Wired. Retrieved April 28, 2016.
24. ^ Piper, Kelsey (November 2, 2018). "Why Elon Musk fears artificial intelligence". Vox. Retrieved March 10, 2021.
25. ^ Lewontin, Max (December 14, 2015). "Open AI: Effort to democratize artificial intelligence research?". The Christian Science Monitor. Retrieved December 19, 2015.
26. ^ Mendoza, Jessica. "Tech leaders launch nonprofit to save the world from killer robots". The Christian Science Monitor.
27. ^ Jump up to:^a b Metz, Cade (December 15, 2015). "Elon Musk's Billion-Dollar AI Plan Is About Far More Than Saving the World". Wired. Retrieved December 19, 2015. Altman said they expect this decades-long project to surpass human intelligence.
28. ^ Vishal Sikka (December 14, 2015). "OpenAI: AI for All". InfyTalk. Infosys. Archived from the original on December 22, 2015. Retrieved December 22, 2015.
29. ^ "OpenAI shifts from nonprofit to 'capped-profit' to attract capital". TechCrunch. March 11, 2019. Retrieved May 10, 2019.
30. ^ Levy, Steven (December 11, 2015). "How Elon Musk and Y Combinator Plan to Stop Computers From Taking Over". Medium/Backchannel. Retrieved December 11, 2015. Elon Musk: ...we came to the conclusion that having a 501(c)(3)... would probably be a good thing to do
31. ^ Brockman, Greg (April 3, 2017). "Yes, we're a 501(c)(3). As you mention in /r/ControlProblem, we will file our 990 later this year as required. Not yet sure of exact date".
32. ^ "Sam Altman's Manifest Destiny". The New Yorker. No. October 10, 2016. Retrieved October 4, 2016.
33. ^ Vincent, James (February 21, 2019). "AI researchers debate the ethics of sharing potentially harmful programs". The Verge. Retrieved March 6, 2020.
34. ^ "Microsoft to invest $1 billion in OpenAI". Reuters. July 22, 2019. Retrieved March 6, 2020.
35. ^ Jump up to:^a b "To Compete With Google, OpenAI Seeks Investors–and Profits". Wired. December 3, 2019. Retrieved March 6, 2020.
36. ^ Jump up to:^a b Kahn, Jeremy (March 11, 2019). "AI Research Group Co-Founded by Elon Musk Starts For-Profit Arm". Bloomberg News. Retrieved March 6, 2020.
37. ^ Murgia, Madhumita (August 7, 2019). "DeepMind runs up higher losses and debts in race for AI". Financial Times. Retrieved March 6, 2020.
38. ^ "OpenAI Will Need More Capital Than Any Non-Profit Has Ever Raised". Fortune. Retrieved March 6, 2020.
39. ^ Vincent, James (July 22, 2019). "Microsoft invests $1 billion in OpenAI to pursue holy grail of artificial intelligence". The Verge. Retrieved March 6, 2020.
40. ^ Haskins, Caroline (March 12, 2019). "OpenAI's Mission to Benefit Humanity Now Includes Seeking Profit". Vice News. Retrieved March 6, 2020.
41. ^ Lee, Dave (October 15, 2019). "Robot solves Rubik's cube, but not grand challenge". BBC News. Retrieved February 29, 2020.
42. ^ Greg Brockman; John Schulman (April 27, 2016). "OpenAI Gym Beta". OpenAI Blog. OpenAI. Retrieved April 29, 2016.
43. ^ "OpenAI Gym". GitHub. Retrieved May 8, 2017.
44. ^ Brockman, Greg (September 12, 2017). "Yep, the Github repo has been the focus of the project for the past year. The Gym site looks cool but hasn't been maintained". @gdb. Retrieved November 7, 2017.
45. ^ "AI Sumo Wrestlers Could Make Future Robots More Nimble". Wired. October 11, 2017. Retrieved November 2, 2017.
46. ^ "OpenAI's Goofy Sumo-Wrestling Bots Are Smarter Than They Look". MIT Technology Review. Retrieved November 2, 2017.
47. ^ Greene, Tristan (May 4, 2018). "OpenAI's Debate Game teaches you and your friends how to lie like robots". The Next Web. Retrieved May 31, 2018.
48. ^ "Why Scientists Think AI Systems Should Debate Each Other". Fast Company. May 8, 2018. Retrieved June 2, 2018.
49. ^ OpenAI; Andrychowicz, Marcin; Baker, Bowen; Chociej, Maciek; Józefowicz, Rafał; McGrew, Bob; Pachocki, Jakub; Petron, Arthur; Plappert, Matthias; Powell, Glenn; Ray, Alex; Schneider, Jonas; Sidor, Szymon; Tobin, Josh; Welinder, Peter; Weng, Lilian; Zaremba, Wojciech (2019). "Learning Dexterous In-Hand Manipulation". arXiv:1808.00177v5 [cs.LG].
50. ^ OpenAI; Akkaya, Ilge; Andrychowicz, Marcin; Chociej, Maciek; Litwin, Mateusz; McGrew, Bob; Petron, Arthur; Paino, Alex; Plappert, Matthias; Powell, Glenn; Ribas, Raphael (2019). "Solving Rubik's Cube with a Robot Hand". arXiv:1910.07113v1 [cs.LG].
51. ^ "Improving Language Understanding by Generative Pre-Training" (PDF). Retrieved June 9, 2020.
52. ^ Jump up to:^a b Hern, Alex (February 14, 2019). "New AI fake text generator may be too dangerous to release, say creators". The Guardian. Retrieved February 14, 2019.
53. ^ Schwartz, Oscar (July 4, 2019). "Could 'fake text' be the next global political threat?". The Guardian. Retrieved July 16, 2019.
54. ^ Vincent, James (February 14, 2019). "OpenAI's new multitalented AI writes, translates, and slanders". The Verge. Retrieved July 16, 2019.
55. ^ "GPT-2: 1.5B Release". OpenAI. November 5, 2019. Retrieved November 14, 2019.
56. ^ "Write With Transformer". Retrieved December 4, 2019.
57. ^ "Talk to Transformer". Retrieved December 4, 2019.
58. ^ "CreativeEngines". Retrieved June 25, 2021.
59. ^ "Language Models are Unsupervised Multitask Learners" (PDF). Retrieved December 4, 2019.
60. ^ Ganesh, Prakhar (December 17, 2019). "Pre-trained Language Models: Simplified". Retrieved September 9, 2020. The intuition behind pre-trained language models is to create a black box which understands the language and can then be asked to do any specific task in that language.
61. ^ "openai/gpt-3". OpenAI. May 29, 2020. Retrieved May 29, 2020.
62. ^ Sagar, Ram (June 3, 2020). "OpenAI Releases GPT-3, The Largest Model So Far". Analytics India Magazine. Retrieved June 14, 2020.
63. ^ Jump up to:^a b c d Brown, Tom; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; Neelakantan, Arvind; Shyam, Pranav; Sastry, Girish; Askell, Amanda; Agarwal, Sandhini (June 1, 2020). "Language Models are Few-Shot Learners". p. appendix. arXiv:2005.14165 [cs.CL].
64. ^ "Language Models are Unsupervised Multitask Learners" (PDF). Retrieved December 4, 2019. GPT-2, is a 1.5B parameter Transformer
65. ^ Brown, Tom; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; Neelakantan, Arvind; Shyam, Pranav; Sastry, Girish; Askell, Amanda; Agarwal, Sandhini (June 1, 2020). "Language Models are Few-Shot Learners". arXiv:2005.14165 [cs.CL]. Since we increase the capacity by over two orders of magnitude from GPT-2 to GPT-3
66. ^ Ray, Tiernan (2020). "OpenAI's gigantic GPT-3 hints at the limits of language models for AI". ZDNet. Retrieved June 5, 2020.
67. ^ Amodei, Dario; Hernandez, Danny (May 16, 2018). "AI and Compute". A petaflop/s-day (pfs-day) consists of performing 10¹⁵ neural net operations per second for one day, or a total of about 10²⁰ operations. The compute-time product serves as a mental convenience, similar to kW-hr for energy.
68. ^ Jump up to:^a b "OpenAI API". OpenAI. June 11, 2020. Retrieved June 14, 2020. Why did OpenAI choose to release an API instead of open-sourcing the models?
    There are three main reasons we did this. First, commercializing the technology helps us pay for our ongoing AI research, safety, and policy efforts. Second, many of the models underlying the API are very large, taking a lot of expertise to develop and deploy and making them very expensive to run. This makes it hard for anyone except larger companies to benefit from the underlying technology. We’re hopeful that the API will make powerful AI systems more accessible to smaller businesses and organizations. Third, the API model allows us to more easily respond to misuse of the technology. Since it is hard to predict the downstream use cases of our models, it feels inherently safer to release them via an API and broaden access over time, rather than release an open source model where access cannot be adjusted if it turns out to have harmful applications.
69. ^ Eadicicco, Lisa. "The artificial intelligence company that Elon Musk helped found is now selling the text-generation software it previously said was too dangerous to launch". Business Insider. Retrieved July 6, 2020.
70. ^ "OpenAI is giving Microsoft exclusive access to its GPT-3 language model". MIT Technology Review. Retrieved September 24, 2020.
71. ^ "Microsoft gets exclusive license for OpenAI's GPT-3 language model". VentureBeat. September 22, 2020. Retrieved September 24, 2020.
72. ^ "Mira Murati via Twitter". Mira Murati. December 5, 2022. Retrieved December 15, 2022.
73. ^ "OpenAI's MuseNet generates AI music at the push of a button". The Verge. April 2019. Retrieved June 8, 2020.
74. ^ "MuseNet". OpenAI. April 25, 2019. Retrieved June 8, 2020.
75. ^ "OpenAI introduces Jukebox, a new AI model that generates genre-specific music". The Verge. April 30, 2020. Retrieved June 8, 2020.
76. ^ Stephen, Bijan (April 30, 2020). "OpenAI introduces Jukebox, a new AI model that generates genre-specific music". Business Insider. Retrieved June 8, 2020.
77. ^ "Jukebox". OpenAI. April 30, 2020. Retrieved June 8, 2020.
78. ^ "TechCrunch Startup and Technology News". TechCrunch. June 11, 2020. Retrieved June 11, 2020. If you’ve ever wanted to try out OpenAI's vaunted machine learning toolset, it just got a lot easier. The company has released an API that lets developers call its AI tools in on "virtually any English language task."
79. ^ "DALL·E: Creating Images from Text". January 5, 2021.
80. ^ "CLIP: Connecting Text and Images". January 5, 2021.
81. ^ "Multimodal Neurons in Artificial Neural Networks". March 4, 2021.
82. ^ "DALL·E 2". OpenAI. Retrieved April 6, 2022.
83. ^ "OpenAI Microscope". April 14, 2020.
84. ^ "OpenAI Microscope". OpenAI Microscope.
85. ^ Jump up to:^a b Alford, Anthony (August 31, 2021). "OpenAI Announces 12 Billion Parameter Code-Generation AI Codex". InfoQ. Retrieved September 3, 2021.
86. ^ Jump up to:^a b Wiggers, Kyle (July 8, 2021). "OpenAI warns AI behind GitHub's Copilot may be susceptible to bias". VentureBeat. Retrieved September 3, 2021.
87. ^ Zaremba, Wojciech (August 10, 2021). "OpenAI Codex". OpenAI. Retrieved September 3, 2021.
88. ^ Dickson, Ben (August 16, 2021). "What to expect from OpenAI's Codex API". VentureBeat. Retrieved September 3, 2021.
89. ^ Claburn, Thomas (August 25, 2021). "GitHub's Copilot may steer you into dangerous waters about 40% of the time – study". The Register. Retrieved September 3, 2021.
90. ^ Savov, Vlad (August 14, 2017). "My favorite game has been invaded by killer AI bots and Elon Musk hype". The Verge. Retrieved June 25, 2018.
91. ^ Frank, Blair Hanley. "OpenAI's bot beats top Dota 2 player so badly that he quits". Venture Beat. Archived from the original on August 12, 2017. Retrieved August 12, 2017.
92. ^ "Dota 2". blog.openai.com. August 11, 2017. Retrieved August 12, 2017.
93. ^ "More on Dota 2". blog.openai.com. August 16, 2017. Retrieved August 16, 2017.
94. ^ Simonite, Tom. "Can Bots Outwit Humans in One of the Biggest Esports Games?". Wired. Retrieved June 25, 2018.
95. ^ Kahn, Jeremy (June 25, 2018). "A Bot Backed by Elon Musk Has Made an AI Breakthrough in Video Game World". Bloomberg.com. Bloomberg L.P. Retrieved June 27, 2018.
96. ^ Clifford, Catherine (June 28, 2018). "Bill Gates says gamer bots from Elon Musk-backed nonprofit are 'huge milestone' in A.I." CNBC. Retrieved June 29, 2018.
97. ^ "OpenAI Five Benchmark". blog.openai.com. July 18, 2018. Retrieved August 25, 2018.
98. ^ Simonite, Tom. "Can Bots Outwit Humans in One of the Biggest Esports Games?". Wired. Retrieved June 25, 2018.
99. ^ Vincent, James (June 25, 2018). "AI bots trained for 180 years a day to beat humans at Dota 2". The Verge. Retrieved June 25, 2018.
100. ^ Savov, Vlad (August 6, 2018). "The OpenAI Dota 2 bots just defeated a team of former pros". The Verge. Retrieved August 7, 2018.
101. ^ Simonite, Tom. "Pro Gamers Fend off Elon Musk-Backed AI Bots—for Now". Wired. Retrieved August 25, 2018.
102. ^ Quach, Katyanna. "Game over, machines: Humans defeat OpenAI bots once again at video games Olympics". The Register. Retrieved August 25, 2018.
103. ^ "The International 2018: Results". blog.openai.com. August 24, 2018. Retrieved August 25, 2018.
104. ^ Statt, Nick (April 13, 2019). "OpenAI's Dota 2 AI steamrolls world champion e-sports team with back-to-back victories". The Verge. Retrieved July 20, 2019.
105. ^ "How to Train Your OpenAI Five". OpenAI Blog. April 15, 2019. Retrieved July 20, 2019.
106. ^ Wiggers, Kyle (April 22, 2019). "OpenAI's Dota 2 bot defeated 99.4% of players in public matches". Venture Beat. Retrieved April 22, 2019.

External links

• Official website