غول هوش مصنوعی گوگل از راه رسید!

جِمینی ۱.۵ پرو؛ مدل نسل بعدیِ هوش مصنوعی گوگل، روی پلتفرم #VertexAI گوگل‌کلاد در دسترسه!

این مدل با درک و تحلیل حجم عظیمی از اطلاعات، به کسب‌وکارها در ساختنِ ربات‌های پشتیبان مبتنی بر هوش مصنوعی کمک می‌کنه!
جِمینی ۱.۵ پرو حتی می‌تونه ورودی‌های صوتی رو هم پردازش کنه، چه موسیقی باشه، چه صحبت‌کردن شخص یا حتی صدای بخشی از ویدئو!
این یعنی جِمینی می‌تونه از صدا متن‌های باکیفیت استخراج کنه یا برای جستجو و آنالیز محتوای ترکیبی (صوت و تصویر) به کار بره.
پس اگه دنبال یه راه‌حل هوش مصنوعیِ فوق‌العاده برای کسب‌وکار خودتون هستین، جِمینی ۱.۵ پرو رو تو VertexAI گوگل‌کلاد از دست ندین!

Imagine this: you write an essay, but instead of a teacher’s red pen, a fancy AI tool grades it. Welcome to the future of education!

آیا هوش مصنوعی آینده آموزش است؟
آیا هوش مصنوعی شغل معلمان را به خطر می‌اندازد؟

Teachers are using AI like ChatGPT to streamline grading, freeing them up for more personalized teaching (think less lecture, more one-on-one guidance). ‍

But hold on a sec… is this a total win? Here’s the flip side:

  • Is AI Grading Fair? AI might struggle with creative writing or complex ideas. ‍♀️
  • Who Owns Your Work? Uploading essays to AI tools raises ethical concerns. Is it a privacy breach?
  • Is This Just a Shortcut? Students using AI to write essays and teachers using AI to grade… is anyone actually learning?

Experts say the key is finding the right balance. AI can be a helpful assistant, but teachers should still be in charge of grading, especially for critical thinking and in-depth analysis.

The Verdict? AI in the classroom is here to stay, but schools need clear guidelines to make sure it’s used ethically and effectively.

What do YOU think? Is AI a friend or foe in education? Share your thoughts in the comments!

Meta Description: AI is invading classrooms! But is it a learning revolution or a grading disaster? This article explores the pros and cons of AI grading and instruction. Is AI a friend or foe in education? Read and share your thoughts! #AIineducation #futureoflearning #teachersandAI

اگه طرفدار ورزش مهیج فوتبال باشید حتما به یاد دارید که در نیمه‌نهایی لیگ قهرمانان 2019، چگونه یک ضربه سریع کرنر توسط ترنت الکساندر-آرنولد، دیووک اوریگی را در موقعیت گلزنی قرار داد و به صحنه‌ای ماندگار تبدیل شد؟

ضربه‌های کرنر میتوانند تبدیل به فرصت‌های بی‌نظیری برای گلزنی شوند، اما داشتن یک برنامه کارآمد برای تحقق آن‌ها نیازمند ترکیبی از هوش انسانی و تحلیل بازی برای شناسایی الگوهای تیم حریف و واکنش آنی است.

حالا به لطف هوش مصنوعی، دستیار باهوشی به کمک مربیان آمده است. محققان گوگل در همکاری با باشگاه لیورپول، سیستم هوش مصنوعی به نام TacticAI را توسعه داده‌اند که می‌تواند به مربیان در زمینه‌ی تاکتیک‌های مربوط به ضربات کرنر مشاوره بدهد.

این سیستم با استفاده از هوش مصنوعی پیش‌بینی‌کننده و مولد، به متخصصان، به‌ویژه در ضربات کرنر، بینش‌های تاکتیکی ارائه می‌دهد. این سیستم با علی‌رغم وجود محدودیت‌هایی در دارابودن داده‌های باکیفیت، با استفاده از رویکرد یادگیری عمیق هندسی به نتایجی در سطح بالا رسیده است.

تحقیقات و ارزیابی  این سیستم با همراهی متخصصان باشگاه لیورپول انجام شده است. جالب اینجاست که پیشنهادات این هوش مصنوعی در 90 درصد موارد نسبت به تاکتیک‌های رایج در زمین، مورد تایید ارزیابان متخصص قرار گرفته است.

TacticAI فراتر از یک دستیار برای ضربات کرنر است. این سیستم نشان داده که تکنیک‌های هوش مصنوعی چگونه می‌توانند دنیای ورزش را برای بازیکنان، مربیان و هواداران متحول کنند.

ورزش‌هایی مانند فوتبال با داشتن تعاملات چندعاملی در دنیای واقعی و با داده‌های چندوجهی، زمینه‌ای ایده‌آل برای توسعه‌ی هوش مصنوعی به شمار می‌روند. پیشرفت‌های به‌دست آمده در حوزه‌ی هوش مصنوعی ورزشی می‌تواند در بسیاری از زمینه‌های درون و بیرون زمین، از بازی‌های رایانه‌ای و رباتیک گرفته تا هماهنگی ترافیک، کاربرد داشته باشد.

TacticAI یک سیستم کامل هوش مصنوعی است که با مدل‌های ترکیبی پیش‌بینی‌کننده و مولد خود، می‌تواند بازی‌های گذشته را تجزیه و تحلیل کرده و برای افزایش احتمال دستیابی به نتایج مورد نظر، در مورد محل قرارگیری و سیستم بازی نیز به مربی پیشنهادهایی بسیار عای می‌دهد.

این سیستم یک گام بلند در بهره‌وری از هوش مصنوعی برای کمک به مربیان فوتبال است و امیدواریم در آینده شاهد توسعه‌ی بیشتر این فناوری و کاربردهای گسترده‌تر آن در ورزش باشیم.



Over 200 renowned musicians, including Billie Eilish, Nicki Minaj, and Stevie Wonder, have signed an open letter expressing their concerns about the “predatory” use of artificial intelligence (AI) that mimics human artists’ voices, likenesses, and sounds.

ai-in-music-opportunity-or-threat
ai-in-music-opportunity-or-threat

Over 200 renowned musicians, including Billie Eilish, Nicki Minaj, and Stevie Wonder, have signed an open letter expressing their concerns about the “predatory” use of artificial intelligence (AI) that mimics human artists’ voices, likenesses, and sounds.

The letter warns against the unbridled use of AI, which they believe could lead to a “race to the bottom” in terms of artistic quality. They call on tech companies to pledge not to develop AI tools that undermine or replace human songwriters and artists.

The use of AI for music production has raised significant concerns. One of the main issues is the training of AI models with artists’ work without their consent. Artists argue that this violates their “intellectual property rights” and undermines the “authenticity of artistic creation.”

Tom Kiehl, CEO of the UK Music organization, agrees with the artists. He says, “Using artists’ work to train AI without their permission is a form of theft.”

On the other hand, some artists have embraced AI. For example, electronic music artist Grimes has allowed her fans to use her voice without restriction in their own works.

So, is AI a threat or an opportunity for the music industry?

The answer is likely complex and multifaceted. AI has the potential to revolutionize music production, making it more efficient and accessible to a wider range of people. However, it also raises important ethical and legal questions that need to be addressed.

It is crucial for the music industry to have a thoughtful and open dialogue about the role of AI. This dialogue should involve artists, tech companies, policymakers, and other stakeholders. Only then can we ensure that AI is used in a way that benefits everyone.


بیلی آیلیش، نیکی میناژ و ۲۰۰ هنرمند مطرح دیگر، نگران استفاده‌ی “غارتگرانه” از هوش مصنوعی در صنعت موسیقی هستند.

این هنرمندان در نامه‌ای سرگشاده، نسبت به استفاده‌ی بی‌رویه از هوش مصنوعی که به عقیده‌ی آن‌ها باعث “کاهش کیفیت آثار هنری” می‌شود، هشدار داده‌اند. آن‌ها از کمپانی‌های فناوری خواسته‌اند که از توسعه‌ی هوش مصنوعی برای ساخت موسیقی که جایگزین هنرمندان شود، خودداری کنند.

استفاده از هوش مصنوعی برای تولید موسیقی، چالش‌های مهمی را به وجود آورده است. آموزش مدل‌های هوش مصنوعی با آثار هنرمندان بدون اجازه‌ی آن‌ها، یکی از این نگرانی‌هاست. هنرمندان معتقدند این کار، “حقوق مادی و معنوی” آن‌ها را نقض می‌کند و به “اصالت آثار هنری” آسیب می‌زند.

تام کیهل، مدیر انجمن موسیقی انگلستان، با هنرمندان موافق است و می‌گوید: «استفاده از آثار هنرمندان برای آموزش هوش مصنوعی بدون اجازه‌ی آن‌ها، نوعی دزدی است.»

از طرف دیگر، برخی هنرمندان هم از هوش مصنوعی استقبال کرده‌اند. برای مثال، Grimes، هنرمند موسیقی الکترونیک، به طرفدارانش اجازه داده تا بدون محدودیت از صدای او در آثارشان استفاده کنند.

نظر شما، هوش مصنوعی در صنعت موسیقی، تهدید است یا فرصت؟

Introducing the groundbreaking advancements in the field of Artificial Intelligence! In this comprehensive post, we delve into the realm of AI excellence, showcasing the top innovators and game-changers that are shaping the future of technology. From cutting-edge research at renowned universities to the latest developments in programming languages, this exploration of AI mastery is sure to captivate and inspire. Join us as we unveil the leaders of the AI frontier and celebrate their remarkable contributions to the world of artificial intelligence. Stay tuned for an insightful journey into the world of AI excellence!

Introducing the groundbreaking advancements in the field of Artificial Intelligence

Topic: Revealing the Global Leaders: A Comprehensive Guide to the Top Universities for Artificial Intelligence (AI)

Topic: Revealing the Global Leaders: A Comprehensive Guide to the Top Universities for Artificial Intelligence (AI)

RankUniversityCountryState/ProvinceAcceptance RateAverage SATAverage ACTNet PriceEnrollmentFounded
1Stanford UniversityUnited StatesCalifornia4%154034$18,279N/AN/A
2University of California – BerkeleyUnited StatesCalifornia11%N/AN/AN/A45,307N/A
3Massachusetts Institute of TechnologyUnited StatesMassachusetts4%155536$20,232N/AN/A
4Carnegie Mellon UniversityUnited StatesPennsylvania11%153035$33,499N/AN/A
5University of Illinois at Urbana – ChampaignUnited StatesIllinois45%141532N/AN/AN/A
6University of Michigan – Ann ArborUnited StatesMichigan18%144033N/AN/AN/A
7University of TorontoCanadaOntarioN/AN/AN/AN/A27,6511827
8Harvard UniversityUnited StatesMassachusetts3%153535$19,491N/AN/A
9Tsinghua UniversityChinaBeijingN/AN/AN/AN/A48,7391911
10University of Washington – SeattleUnited StatesWashington48%N/AN/AN/A52,319N/A
11University of OxfordUnited KingdomEngland22%N/AN/AN/AN/A1096
12University College LondonUnited KingdomEnglandN/AN/AN/AN/A42,0001826
13University of California – Los AngelesUnited StatesCalifornia9%N/AN/AN/A46,430N/A
14University of Maryland – College ParkUnited StatesMaryland45%144032N/AN/AN/A
15Cornell UniversityUnited StatesNew York State7%152034$26,060N/AN/A
16Georgia Institute of TechnologyUnited StatesGeorgia17%146033N/AN/AN/A
17University of CambridgeUnited KingdomEngland21%N/AN/AN/AN/A1209
18University of Southern CaliforniaUnited StatesCalifornia12%150034$36,808N/AN/A
19University of Wisconsin – MadisonUnited StatesWisconsin49%142529N/AN/AN/A
20University of California-San DiegoUnited StatesCalifornia24%N/AN/AN/A42,006N/A
21Nanyang Technological UniversitySingaporeSingapore CityN/AN/AN/AN/A33,0001955
22University of Texas at AustinUnited StatesTexas31%136530N/AN/AN/A
23National University of SingaporeSingaporeSingapore CityN/AN/AN/AN/A30,0981905
24University of PennsylvaniaUnited StatesPennsylvania7%153535$26,123N/AN/A
25Harbin Institute of TechnologyChinaHarbin16%N/AN/AN/AN/A1920
26Princeton UniversityUnited StatesNew Jersey6%153534$18,698N/AN/A
27Shanghai Jiao Tong UniversityChinaShanghaiN/AN/AN/AN/A47,0001896
28Johns Hopkins UniversityUnited StatesMaryland7%154535$24,034N/AN/A
29University of Minnesota – Twin CitiesUnited StatesMinnesota75%139530N/AN/AN/A
30Imperial College LondonUnited KingdomEnglandN/AN/AN/AN/A17,5651907
31Columbia UniversityUnited StatesNew York State4%153535$22,058N/AN/A
32University of British ColumbiaCanadaBritish Columbia52%N/AN/AN/A20,8931908
33Pennsylvania State UniversityUnited StatesPennsylvania55%130029N/AN/AN/A
34Federal Institute of Technology LausanneSwitzerlandLausanneN/AN/AN/AN/A12,576N/A
35New York UniversityUnited StatesNew York State12%152034$29,499N/AN/A
36University of TokyoJapanTokyo36%N/AN/AN/A28,2181877
37Swiss Federal Institute of Technology ZurichSwitzerlandZurich8%N/AN/AN/A23,420N/A
38Catholic University of LeuvenBelgiumLeuvenN/AN/AN/AN/A62,6931425
39Ohio State UniversityUnited StatesOhio53%139531N/AN/AN/A
40University of Hong KongChinaHong Kong17%N/AN/AN/A21,6521911
41Yale UniversityUnited StatesConnecticut5%154034$18,647N/AN/A
42Zhejiang UniversityChinaHangzhouN/AN/AN/AN/A60,7391897
43Technical University of MunichGermanyBavaria46%N/AN/AN/A44,0001868
44Beihang UniversityChinaBeijingN/AN/AN/AN/AN/A1952
45Delft University of TechnologyNetherlandsDelft50%N/AN/AN/A24,7031842
46Purdue UniversityUnited StatesIndiana53%133531N/AN/AN/A
47Huazhong University of Science and TechnologyChinaWuhanN/AN/AN/AN/A71,9701953
48Arizona State University – TempeUnited StatesArizona90%N/AN/AN/A80,065N/A
49University of WaterlooCanadaOntarioN/AN/AN/AN/A35,9001957
50University of ManchesterUnited KingdomEnglandN/AN/AN/AN/AN/A1824
Data-Driven Insights: Unlocking Business Value through Analytics Online Visibility**

RankUniversityCountryRegionAcceptance RateAverage SATAverage ACTNet PriceEnrollmentFounded
51University of California, BerkeleyUnited StatesNorth America15%143033$13,451N/AN/A
52University of TorontoCanadaNorth America43%N/AN/AN/A88,3321827
53University of EdinburghUnited KingdomEuropeN/AN/AN/AN/A31,2951583
54University of MelbourneAustraliaOceaniaN/AN/AN/AN/A50,1741853
55University of ManchesterUnited KingdomEuropeN/AN/AN/AN/A39,1801824
56University of GlasgowUnited KingdomEuropeN/AN/AN/AN/A26,6001451
57University of WashingtonUnited StatesNorth America44%134031N/AN/AN/A
58University of California, Los AngelesUnited StatesNorth America12%140532$15,763N/AN/A
59University of BristolUnited KingdomEuropeN/AN/AN/AN/A24,5301909
60University of BirminghamUnited KingdomEuropeN/AN/AN/AN/A29,5401900
61University of WarwickUnited KingdomEuropeN/AN/AN/AN/A27,6401965
62University of LeedsUnited KingdomEuropeN/AN/AN/AN/A35,5001904
63University of NottinghamUnited KingdomEuropeN/AN/AN/AN/A33,3901881
64University of SouthamptonUnited KingdomEuropeN/AN/AN/AN/A25,0301862
65University of SheffieldUnited KingdomEuropeN/AN/AN/AN/A27,0001905
66Seoul National UniversitySouth KoreaAsia20%N/AN/AN/A28,3781946
67University of Massachusetts – AmherstUnited StatesNorth America64%137031N/AN/AN/A
68Northwestern UniversityUnited StatesNorth America7%153034$22,095N/AN/A
69Beijing Institute of TechnologyChinaAsiaN/AN/AN/AN/A27,0001940
70National Taiwan UniversityTaiwanAsiaN/AN/AN/AN/A31,7991945
71University of North Carolina at Chapel HillUnited StatesNorth America17%144032N/AN/AN/A
72Wuhan UniversityChinaAsiaN/AN/AN/AN/A60,0001893
73Northwestern Polytechnical UniversityChinaAsia20%N/AN/AN/A29,0001938
74RWTH Aachen UniversityGermanyEuropeN/AN/AN/AN/A47,5211870
75Vienna University of TechnologyAustriaEuropeN/AN/AN/AN/A29,3411872
76Boston UniversityUnited StatesNorth America14%142533$27,829N/AN/A
77University of Science and Technology of ChinaChinaAsia10%N/AN/AN/AN/A1958
78Kyoto UniversityJapanAsia11%N/AN/AN/A22,4551897
79City University of Hong KongChinaAsia36%N/AN/AN/AN/A1984
80Xidian UniversityChinaAsiaN/AN/AN/AN/A35,2771931
81University of MontrealCanadaNorth America41%N/AN/AN/A66,9721878
82University of QueenslandAustraliaOceaniaN/AN/AN/AN/A48,7711909
83Australian National UniversityAustraliaOceania71%N/AN/AN/AN/A1946
84Hong Kong University of Science and TechnologyChinaAsia34%N/AN/AN/AN/A1991
85University of California, DavisUnited StatesNorth America43%133031N/AN/AN/A
86University of California, San DiegoUnited StatesNorth America33%137032N/AN/AN/A
87University of California, Santa BarbaraUnited StatesNorth America34%138032N/AN/AN/A
88University of California, IrvineUnited StatesNorth America39%136032N/AN/AN/A
89University of California, RiversideUnited StatesNorth America56%128030N/AN/AN/A
90University of California, MercedUnited StatesNorth America76%119028N/AN/AN/A
91University of WaterlooCanadaNorth America54%N/AN/AN/A39,5201957
92University of AlbertaCanadaNorth America52%N/AN/AN/A39,3631908
93University of British ColumbiaCanadaNorth America50%N/AN/AN/A65,1211908
94University of CalgaryCanadaNorth America55%N/AN/AN/A33,2861966
95University of SaskatchewanCanadaNorth America63%N/AN/AN/A26,0771907
96University of ManitobaCanadaNorth America65%N/AN/AN/A31,4041877
97University of Western OntarioCanadaNorth America56%N/AN/AN/A31,4831878
98University of OttawaCanadaNorth America55%N/AN/AN/A42,3141848
99University of VictoriaCanadaNorth America64%N/AN/AN/A21,7411963
100University of GuelphCanadaNorth America60%N/AN/AN/A29,2701964
The Enchanting World of Fairy Tales: Exploring the Timeless Magic

Best 5 Notebooks for AI Development in 2023 for AI Development: Power, Performance, and Portability

NotebookTypeProcessorGraphicsRAMStorageDisplayBattery LifePrice
Apple MacBook Pro 16-inch (M1 Max/Pro)LaptopApple M1 Max/ProIntegratedUp to 64GBUp to 8TB16.2-inch Liquid Retina XDRUp to 21 hoursStarting at $2,499
Dell XPS 15 (Alder Lake)LaptopUp to 12th Gen Intel Core i9NVIDIA GeForce RTX 3050 TiUp to 32GBUp to 2TB15.6-inch OLEDUp to 16 hoursStarting at $1,299
HP Spectre x360 14 (12th Gen Intel Core/NVIDIA GeForce RTX 3050)2-in-1 LaptopUp to 12th Gen Intel Core i7NVIDIA GeForce RTX 3050Up to 16GBUp to 1TB14-inch OLEDUp to 10 hoursStarting at $1,199
Microsoft Surface Laptop Studio (Intel Evo/NVIDIA GeForce RTX 3050 Ti)2-in-1 LaptopUp to Intel Evo i7NVIDIA GeForce RTX 3050 TiUp to 32GBUp to 2TB14.4-inch PixelSense touchscreenUp to 19 hoursStarting at $1,599
Lenovo ThinkPad X1 Carbon Gen 10 (Intel Alder Lake)LaptopUp to 12th Gen Intel Core i7Optional NVIDIA GeForce RTXUp to 32GBUp to 2TB14-inch Dolby Vision OLEDUp to 15 hoursStarting at $1,299
Best 5 Notebooks for AI Developers

Transforming the landscape of image generation, Ideogram AI unveils Ideogram 1.0, a revolutionary tool with cutting-edge features like top-tier text rendering and unparalleled photorealism. Backed by a Series A funding of $80 million, Ideogram sets a new standard in prompt adherence and image quality, positioning itself as a leader in text-to-image generation.

https://ideogram.ai/


Ideogram AI: Revolutionizing Image Generation with Ideogram 1.0

Ideogram AI, a cutting-edge startup founded by former Google engineers and esteemed members from UC Berkeley, Carnegie Mellon University, and the University of Toronto, has unveiled its groundbreaking image generator, Ideogram 1.0.

Advanced Features of Ideogram 1.0

In an official announcement, Ideogram AI expressed their enthusiasm for the release of Ideogram 1.0. This latest version boasts top-tier text rendering, unparalleled photorealism, and prompt adherence. Additionally, it introduces the innovative Magic Prompt feature for crafting detailed prompts that inspire beautiful, imaginative images.

Funding and Recognition

The debut of Ideogram 1.0 coincides with a significant milestone—a Series A funding round of $80 million, spearheaded by Andreessen Horowitz and supported by Redpoint Ventures, Pear VC, and SV Angel.

Evaluation and Performance

Decrypt’s evaluation of Ideogram’s capabilities revealed a substantial leap forward in version 1.0, surpassing its predecessors in prompt adherence, image quality, and text generation prowess. While the model’s internal workings remain proprietary, its performance speaks volumes, positioning it as a leading contender in the field—until the anticipated release of Stable Diffusion 3.

Competitive Edge and Pricing

Ideogram sets itself apart with its prowess in text generation, outshining competitors like Dall-E 3 and MidJourney. It offers a free tier and paid plans starting at $7 per month, providing access to advanced features such as an image editor, enhanced downloads, and private generation options.

Standout Feature: “Prompt Magic”

A standout feature of Ideogram is “Prompt Magic,” a versatile tool that enhances prompts for superior image quality. This feature gives users the flexibility to toggle it on or off. Testers have shown a preference for Ideogram over other models, citing its excellence in prompt alignment, image coherence, and text rendering quality.

Superior Performance

In a side-by-side comparison with MidJourney and Dall-E 3, Ideogram excelled in understanding complex prompts and spatial relationships. It showcased superior prompt adherence and spatial comprehension. Ideogram’s ability to interpret intricate scenes with precision and creativity sets it apart as a top choice for text-to-image generation.

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  • Outbound Links: https://ideogram.ai
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  • Keyphrase Length: Ideogram AI, Image Generation, Ideogram 1.0, Text Rendering, Photorealism, Magic Prompt, Series Funding, Decrypt Evaluation, Competitive Edge, Prompt Magic
رقیبی قدرتمند برای میدجرنی و دالی 3
به تازگی استارت‌آپی به نام Ideogram AI منتشر شده که یک تولیدکننده تصویر است و میتواند رقیبی جدی برای MidJourney و Dall-E 3 باشد.

Sora is an artificial intelligence model capable of generating lifelike and creative visual representations based on textual prompts. This innovative technology utilizes advanced algorithms to interpret and translate written instructions into visually compelling images.

All videos on this page were generated directly by Sora without modification.

The tool was developed by OpenAI. It is designed to teach artificial intelligence to understand and simulate the physical world in motion, with the ultimate goal of training models that can assist individuals in solving problems requiring real-world interaction.

Introducing Sora, the text-to-video model created by OpenAI. Sora has the ability to generate videos up to one minute in length while maintaining high visual quality and adhering to the user’s instructions.

Sora possesses the capability to create intricate visuals featuring numerous characters, precise movements, and detailed subject and background elements. The AI comprehends not just the user’s prompt but also the real-world representation of the requested elements, showcasing a high level of professionalism and expertise in the field of SEO.

Leveraging its profound language comprehension, the model adeptly interprets prompts to craft dynamic characters imbued with vivid emotions. Sora’s ability to seamlessly integrate multiple scenes in a single video, maintaining consistency in character portrayal and visual aesthetics, demonstrates a high level of SEO-optimized proficiency.

The existing model exhibits limitations in its capabilities. It may encounter challenges in authentically replicating the physics of intricate scenarios and could falter in recognizing precise cause-and-effect relationships. An instance of this deficiency could be illustrated when a person consumes a portion of a cookie, yet the resulting visual lacks the intended bite mark.

Furthermore, spatial intricacies within prompts may cause confusion for the model, leading to potential errors in distinguishing between left and right orientations. Additionally, articulating detailed sequences of events unfolding over time, such as tracking a specific camera path, might pose difficulties for the model’s SEO performance.

Prior to the integration of Sora into OpenAI’s products, a series of critical safety measures will be implemented. Collaborating with red teamers—experts in domains such as misinformation, offensive content, and bias—we will subject the model to adversarial testing to ensure its robustness.

To enhance content scrutiny, we are developing specialized tools, including a detection classifier capable of identifying videos generated by Sora. Future plans involve incorporating C2PA metadata if the model is deployed within an OpenAI product.

In tandem with the creation of novel safety protocols for deployment, we are leveraging existing safety mechanisms utilized in products featuring DALL·E 3, which are equally applicable to Sora. For example, within an OpenAI product, our text classifier will vet and reject prompts breaching usage policies, encompassing requests for explicit violence, sexual material, offensive imagery, celebrity likenesses, or third-party intellectual property. Additionally, robust image classifiers will be employed to scrutinize every video frame to ensure compliance with our usage guidelines before user presentation.

Engagement with policymakers, educators, and artists globally will be prioritized to address concerns and highlight positive applications of this groundbreaking technology. Despite exhaustive research and testing, the full spectrum of beneficial and potentially harmful uses remains unpredictable. Hence, we emphasize the significance of real-world feedback in refining and releasing progressively secure AI systems.

ویدئوهای آموزش هوش مصنوعی – زبان انگلیسی Want to understand Large Language Models?


Stanford CS25: V1 I Transformers United: DL Models that have revolutionized NLP, CV, RL

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Stanford CS25: V1 I Transformers in Language: The development of GPT Models, GPT3

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Stanford CS25: V1 I Transformers in Vision: Tackling problems in Computer Vision

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Stanford CS25: V1 I Decision Transformer: Reinforcement Learning via Sequence Modeling

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Stanford CS25: V1 I Mixture of Experts (MoE) paradigm and the Switch Transformer

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Stanford CS25: V1 I DeepMind’s Perceiver and Perceiver IO: new data family architecture

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Stanford CS25: V1 I Self Attention and Non-parametric transformers (NPTs)

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Stanford CS25: V1 I Transformer Circuits, Induction Heads, In-Context Learning

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Stanford CS25: V1 I Audio Research: Transformers for Applications in Audio, Speech, Music

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Stanford CS25: V2 I Represent part-whole hierarchies in a neural network, Geoff Hinton

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Stanford CS25: V2 I Introduction to Transformers w/ Andrej Karpathy

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Stanford CS25: V2 I Language and Human Alignment

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Stanford CS25: V2 I Emergent Abilities and Scaling in LLMs

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Stanford CS25: V2 I Strategic Games

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Stanford CS25: V2 I Robotics and Imitation Learning

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Stanford CS25: V2 I Common Sense Reasoning

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Stanford CS25: V2 I Biomedical Transformers

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Stanford CS25: V2 I Neuroscience-Inspired Artificial Intelligence

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Stanford CS25: V3 I Low-level Embodied Intelligence w/ Foundation Models

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Stanford CS25: V3 I Generalist Agents in Open-Ended Worlds

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Stanford CS25: V3 I How I Learned to Stop Worrying and Love the Transformer

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Stanford CS25: V3 I Recipe for Training Helpful Chatbots

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Stanford CS25: V3 I No Language Left Behind: Scaling Human-Centered Machine Translation

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Stanford CS25: V3 I Beyond LLMs: Agents, Emergent Abilities, Intermediate-Guided Reasoning, BabyLM

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Stanford CS25: V3 I Retrieval Augmented Language Models

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More details about the course:

https://web.stanford.edu/class/cs25/

The use of artificial intelligence is a crucial aspect that has been greatly enhanced by the remarkable growth of ChatGPT, symbolizing this new technological revolution.

Artificial intelligence works when you install software or applications on your system that utilize AI to perform tasks that would otherwise require human intervention, such as learning, reasoning, problem-solving, decision-making, and natural language processing.

Some common examples of AI software include chatbots, virtual assistants, recommendation engines, image and speech recognition software, and predictive analytics tools. There are many in this industry, and if you are looking to get started, this article covers ten of the top general AI software tools.

One standout among the best AI-powered website building tools is Hostinger. Its AI-based suite covers a variety of capabilities and makes website creation easy. Hostinger’s user-friendly interface, supported by AI, enables anyone to design and launch amazing websites. With Hostinger’s AI tools, you can enhance productivity, save time, and achieve significant results.

Common features of AI software can vary widely depending on the specific application and technology they utilize. Here are a few common and innovative features you can expect:

Machine learning algorithms are essentially what powers artificial intelligence. They often use complex algorithms to analyze data, learn from it, and make predictions or decisions based on that analysis.

Natural language processing (NLP) is a key component of many AI software tools, enabling them to understand and interpret human language, whether written or spoken.

Computer vision allows AI software to interpret and understand the content of visual data, such as images and videos, opening up a wide range of applications in fields like healthcare, automotive, and retail.

Predictive analytics uses AI to analyze data and make predictions about future events or outcomes, helping businesses make informed decisions and optimize their strategies.

These are just a few examples of the capabilities and features that AI software can offer, and the field is rapidly evolving with new advancements and innovations.

  • TensorFlow:
    The Perfect Machine Learning Framework for Newbies and Experts Alike. With its flexibility, scalability, and support for various tasks including deep learning, neural networks, and natural language processing, TensorFlow is widely used in industries such as healthcare, finance, and transportation. This software is designed to optimize performance with both CPUs and GPUs, allowing developers to build models using a variety of techniques. With its wide range of functions for building and training models, TensorFlow is easy to use and offers high-level APIs for quick testing and deployment. Best of all, it’s free to use!

  • Salesforce Einstein
    Salesforce Einstein: Empower Your Business with AI-Driven Customer Insights and Automation. Salesforce Einstein is a robust software offering predictive analytics, natural language processing, and automation capabilities to enhance customer relationship management. With its predictive analytics, businesses can gain valuable insights into customer behavior, while its natural language processing feature automatically analyzes and classifies customer feedback. Additionally, automated task functions and personalization options contribute to increased productivity and customer satisfaction. However, the implementation and maintenance of Salesforce Einstein may require additional time and resources, and some users may find it challenging to use. Explore its potential with a 30-day free trial, and reach out to the company for custom pricing based on a pay-per-feature model.

  • PyTorch
    PyTorch: Empowering Researchers and Developers with Cutting-Edge Deep Learning Capabilities. As an open-source machine learning library developed by Facebook’s AI Research team (FAIR), PyTorch has garnered widespread acclaim for its user-friendly Pythonic API, making it an ideal choice for both novice and experienced developers. Its seamless integration with popular Python libraries like NumPy, SciPy, and Pandas facilitates data preprocessing and analysis. With applications spanning computer vision, natural language processing (NLP), and speech recognition, PyTorch supports diverse tasks including image classification, object detection, machine translation, and text generation. Best of all, PyTorch is freely available as open-source software, fostering a vibrant community of contributors and users.

  • H2O.ai
    H2O.ai: Empowering Businesses with Scalable and Efficient Machine Learning Solutions. Since its inception in 2012, H2O.ai has been a go-to software company for businesses seeking to build machine learning algorithms, including generalized linear modeling, deep learning, and gradient boosting. With its user-friendly interface, intuitive workflows, and distributed computing capabilities, H2O.ai’s platforms are well-suited for enterprise-level applications. Its optimized algorithms and active community of users, developers, and contributors ensure top-notch performance and support. While it’s important to evaluate your needs and goals, H2O.ai is an excellent choice for a flexible and powerful machine-learning platform. New users can take advantage of a 90-day free trial before switching to a per-feature pricing model. Contact the company for custom pricing.

  • Infosys Nia
    “Infosys Nia: Transforming Businesses with Advanced AI-Powered Cloud Solutions. Infosys Nia stands out as a leading AI-powered cloud-based platform, offering organizations advanced capabilities in machine learning, cognitive automation, and analytics. With features like natural language processing, image recognition, and predictive analytics, the platform empowers businesses to seize new opportunities and foster growth. Its robotic process automation, virtual agents, and knowledge management functionalities drive operational efficiency and enhance user experiences. Infosys Nia operates on a per-feature pricing model, and businesses can contact the company for custom pricing.”