




版權(quán)說明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請進(jìn)行舉報或認(rèn)領(lǐng)
文檔簡介
Copilot
for
R/revodavid/copilot-for-r@revodavid
at@NYHACKRwhat
it
doeshow
to
use
it,
andhow
it
worksDavid
Smith
(@revodavid)Principal
Cloud
AdvocateMicrosoftTalk
Notes:/revodavid/copilot-for-rUses
the
context
you’ve
providedand
synthesizes
code
to
matchConvert
comments
to
codeAutofill
for
repetitive
codeAutosuggest
testsShow
alternativesGitHubCopilotYour
AI
pair
programmer/revodavid/copilot-for-r@revodavid
at@NYHACKRaka.ms/get-copilot/revodavid/copilot-for-r@revodavid
at@NYHACKR/revodavid/copilot-for-r@revodavid
at@NYHACKRR
Pumpkins
Demo/revodavid/copilot-for-r@revodavid
at@NYHACKR/revodavid/copilot-for-r@revodavid
at@NYHACKRGenerative
AI
Models/revodavid/copilot-for-r@revodavid
at@NYHACKRGenerative
AIPrompt:Write
a
tagline
for
an
ice
creamshop.Response:We
serve
up
smiles
with
everyscoop!Prompt:Table
customers,
columns
=[CustomerId,
FirstName,LastName,
Company,
Address,City,
State,
Country,PostalCode]Create
a
SQL
query
for
allcustomers
in
Texas
named
Janequery=Response:SELECT
*FROM
customersWHERE
State
=
'TX'
AND
FirstName=
'Jane'Response:GPT-3CodexDALL·EPrompt:
A
white
Siamese
catGenerative
AIcan:Generate
text,
images
and
codeDifferent
models
aretrained
on
different
corpuses,depending
on
the
application.Generate
“humanlike”
outputWhat
is
a
likelycontinuation
of
the
prompt,
giventhe
training
data?/revodavid/copilot-for-r@revodavid
at@NYHACKRExtract
informationThe
continuation
is
likely
to
be
similar
to
textfrequently
represented
in
thetraining
data.Createnovel
contentText,
images
and
code
not
contained
in
its
trainingset.
Translations.“Creative”
works.IntelligentIt’sjust
a
predictivesystem,
designed
to
give
a
likelycontinuation
of
the
prompt
given
the
training
data.DeterministicRun
the
same
prompt.
Get
back
a
differentresponse
(probably)./revodavid/copilot-for-r@revodavid
at@NYHACKRTrustworthyIt
can
“hallucinate”facts
andconfidently
assertthem
to
be
true.Generative
AIis
not:TODOLearnThe
model
is
fixed
at
the
time
of
its
training./revodavid/copilot-for-r@revodavid
at@NYHACKRContain
all
of
the
information
of
itstraining
setThink:a
blurry
jpeg
of
its
training
data.Include
verbatim
copies
of
its
trainingdataBut
it
can
generate
stuff
that
looks
like
it.Generative
AIdoes
not:Generative
AIdoesn’t:Understand
languageIt’s
just
a
predictive
engine.
Itdoesn’t
understandmath,either.Understand
factsMany
predictions
echo
information
inthe
trainingset,but
this
is
not
guaranteed./revodavid/copilot-for-r@revodavid
at@NYHACKRUnderstand
manners,
emotion
orethicsAlso:
avoid
anthropomorphizingit.Understand
anythingIt’s
just
a
prediction
engine!Prompt
–
Text
input
thatprovides
some
context
to
theengine
on
what
isexpecting.Completion
–
Output
thatGPT-3
generatesbasedonthe
prompt
and
the
trainedmodel.Prompt
Engineering
(very
briefly)Ensure
that
artificialgeneral
intelligence
(AGI)benefits
humanity.Empowerevery
person
andorganization
on
the
planetto
achieve
moreGPT-3Generate
and
UnderstandTextCodexGenerate
and
Understand
CodeDALL·EGenerate
images
from
textprompts/revodavid/copilot-for-r@revodavid
at@NYHACKRDemo:
Azure
OpenAI
Service/revodavid/copilot-for-r@revodavid
at@NYHACKRof
new
code
written
with
CopilotGitHubCopilotOnce
enabled…40%/revodavid/copilot-for-r@revodavid
at@NYHACKRof
devsfelt
morefulfilled
with
their
jobs87%of
devs
said
it
helpedpreserve
mental
effort75%Azure
OpenAI
ServiceGPT-3CodexDALL·E
(preview)/revodavid/copilot-for-r@revodavid
at@NYHACKRThank
you!/revodavid/copilot-for-r@revodavid
at@NYHACKRaka.ms/get-copilot/revodavid/copilot-for-rDavid
Smith
(@revodavid)Principal
Cloud
Advocate,
MicrosoftBonus
slides/revodavid/copilot-for-r@revodavid
at@NYHACKRFor
Q&A1956Artificial
Intelligence1997Machine
Learning2017Deep
Learning2021Generative
AIReliability
&
SafetyPrivacy
&
SecurityFairnessOurPrinciplesInclusivenessTransparencyAccountability@revodavid
at@NYHACKR/revodavid/copilot-for-rInferencing
timeCapabilityCurieAnswering
questionsComplex,
nuanced
classificationDavinciSummarizing
forspecific
audienceGenerating
creative
contentBabbageSemantic
searchrankingModeratelycomplexclassificationAdaSimple
classificationParsing
and
formatting
textAzure
OpenAI
Service
modelsCushman-codexDavinci-codexCapabilityCodexGPT-3ModelRequestDescription,
performance,
costUse
casesDavinci4,000
tokensMost
capable
GPT-3model.
Can
doComplex
intent,
cause
andany
task
the
other
models
can
do,effect,
summarization
foroften
with
higher
quality,
longer
outputaudienceand
better
instruction-following.Curie2048
tokensVery
capable,
but
faster
and
lower
costLanguage
translation,than
Davinci.complex
classification,textsentiment,
summarizationBabbage2048
tokensCapable
of
straightforward
tasks,
veryModerate
classification,fast,
and
lower
cost.semantic
search
classificationAda2048
tokensCapable
of
very
simple
tasks,
usuallyParsing
text,
simplethe
fastest
model
in
the
GPT-3
series,classification,
addressand
lowest
cost.correction,
keywordsAzure
OpenAI
|
GPT-3
Family
of
ModelsAccelerates
software
developmentMakes
APIs
moreaccessibleWidens
who
can
codeOpenAI
CodexOpenAI
Codex
ModelsDerived
from
base
models
and
trained
on
bothNLand
code
(billions
ofLines
ofCode)Supp
溫馨提示
- 1. 本站所有資源如無特殊說明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請下載最新的WinRAR軟件解壓。
- 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
- 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁內(nèi)容里面會有圖紙預(yù)覽,若沒有圖紙預(yù)覽就沒有圖紙。
- 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
- 5. 人人文庫網(wǎng)僅提供信息存儲空間,僅對用戶上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理,對用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對任何下載內(nèi)容負(fù)責(zé)。
- 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容,請與我們聯(lián)系,我們立即糾正。
- 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時也不承擔(dān)用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。
最新文檔
- 二零二五年度競業(yè)協(xié)議失效一個月競業(yè)限制解除補償合同
- 二零二五年度大型商場裝修合同(含室內(nèi)外環(huán)境美化)
- 二零二五年度特色主題展臺設(shè)計制作安裝一體化合同
- 二零二五年度紋身技藝培訓(xùn)與加盟合作協(xié)議
- 二零二五年度新能源產(chǎn)業(yè)臨時研發(fā)人員服務(wù)協(xié)議
- 2025年度網(wǎng)絡(luò)安全防護(hù)合同價款調(diào)整與網(wǎng)絡(luò)安全事件應(yīng)對
- 二零二五年度虛擬現(xiàn)實產(chǎn)業(yè)利潤分配協(xié)議書
- 二零二五年度搏擊教練員免責(zé)責(zé)任書
- 農(nóng)業(yè)現(xiàn)代化技術(shù)推廣合作協(xié)議
- 智能建筑系統(tǒng)合同
- 2023年全國高考體育單招考試英語試卷試題真題(精校打印版)
- 2023年四川省綿陽市中考化學(xué)試卷真題(含答案與解析)
- 財務(wù)管理中的財務(wù)指標(biāo)
- 2016-2023年青島酒店管理職業(yè)技術(shù)學(xué)院高職單招(英語/數(shù)學(xué)/語文)筆試歷年參考題庫含答案解析
- 第二章-環(huán)境數(shù)據(jù)統(tǒng)計與分析
- 電力各種材料重量表總
- 腸道健康講座活動策劃
- 醫(yī)療器械(耗材)項目投標(biāo)服務(wù)投標(biāo)方案(技術(shù)方案)
- 小學(xué)三年級下冊數(shù)學(xué)教案3篇
- pci術(shù)后術(shù)肢腫脹處理流程
- 遼寧省營口市2023-2024學(xué)年七年級上學(xué)期期末英語試題
評論
0/150
提交評論