Mindmap: что это и как составить интеллект-карту

Пользоваться сервисом можно без регистрации, бесплатно. Его минусом является отсутствие русскоязычной версии. А в Lucidchart или MindMaster достаточно потянуть за родительский блок, чтобы все дочерние блоки вместе со стрелками и примечаниями последовали за ним. Кстати, в той же Ручное тестирование MindMaster есть удобный поиск по лучшим картам, которые в программе создали другие пользователи.

Ментальная карта для писателей .Регулярно обновляйте карту.

Майнд-карты — невероятно полезный инструмент, который помогает всем. Они упрощают, разгружают голову, помогают сократить время на изучение чего-то нового. Таким инструментом всегда можно пользоваться бесплатно — нужны только ручка и карандаш. Советуем использовать разные цвета и длину линий. В голове не может быть все систематизировано и забито в однообразную таблицу, поэтому в майнд-карте тоже не должно. Тем более с помощью разных цветов легче запоминать ментальная карта это большой объем информации.

Какие задачи поможет решить mind map

Сервис без возможности совместного редактирования в реальном времени, поэтому его лучше использовать индивидуально, без работы в команде. Предлагает полный набор инструментов для мышления и формирования идей. https://deveducation.com/ Интеллект карты можно использовать для решения множества задач в бизнесе или в обычной жизни. Они помогут построить визуальное и предельно понятное представление рабочего процесса. По информации разработчиков, сервисом Lucidchart пользуется более 15 млн человек в 180 странах.

Mindmap: как использовать интеллект-карты

  • Также на бумаге нужно обязательно фиксировать все мысли, которые могут возникнуть в ходе составления карты.
  • Карту используют во всех сферах, чтобы запомнить, придумать, разобраться, визуализировать, найти связи и разгрузиться.
  • Простыми словами, mind map делает информацию более понятной и запоминающейся.
  • Майнд карты представляют собой схематичное выражение ваших мыслей, планов и способов решения проблемы, путем построения последовательности системных связей.
  • Вам будут выскакивать подсказки на английском языке.

В центре листка пишем главную цель или проблему, которую необходимо решить. Вокруг основной цели«солнышком» записываются все методы и способы, которые помогут достичь цели. Также на бумаге нужно обязательно фиксировать все мысли, которые могут возникнуть в ходе составления карты. Допустим, вы хотите успешно закончить учебный семестр. Расположите эти подзадачи вокруг основой цели, и соедините их с целью стрелками.

Какими еще можно пользоваться сервисами

Главное — чтобы слова работали на запоминание и не путали вас. Если вы управляете большим проектом, интеллект-карты делают так, что все члены вашей команды видят задачу, ее пункты и подпункты, знают свои сроки и зону ответственности. А вы тем временем можете развивать свой бизнес и придумывать больше успешных проектов. Есть бесплатная версия с 3 картами, личный аккаунт можно получить за $4,99, Pro — за $8,25 и бизнес-аккаунт — за $12,49.

Детектив долго смотрит в эту доску, внезапно кричит «Эврика» и бежит обличать преступника. В сервисе есть бесплатный тариф, но с ограниченным количеством функций. Чтобы передавать доступ другим пользователям нужно заплатить 19.99$ за 3 месяца или 59.99$ за год. Ментальные карты позволяют охватить большой объем информации и систематизировать её. Студенты могут быстро пробежаться по ключевым понятиям и связям перед экзаменом. Карты гораздо компактнее, чем классические конспекты или учебники, так что за меньшее время получится повторить больше материала.

Авторы книг, сценаристы и журналисты могут использовать ментальные карты для планирования своих историй, персонажей и сюжетных линий. Студенты могут использовать ментальные карты для создания конспектов лекций или учебных материалов. Визуальная структура помогает лучше запоминать и понимать материалы, особенно в сложных предметах. Это подтемы — блоки, которые напрямую связаны с основной идей mindmap. Например, это направления анализа конкурентов. Создаём четыре блока и даём им короткие точные названия — лучше ограничиться парой слов.

Человеческий мозг лучше запоминает данные, представленные в отдельных блоках, чем сплошной текст.

В этой программе можно нарисовать ментальную карту с нуля или воспользоваться готовым шаблоном. В записи можно вставлять файлы, изображения или даже видео. Есть кооперативный доступ, одновременно может работать неограниченное число пользователей. Они помогают все знания разложить по полочкам и обобщить полученную информацию в систему. Незатейливый онлайн-сервис для создания интеллект-карт.

майндмэп это

Еще одна рекомендация — более крупным шрифтом выделять более значимые связи и названия элементов, а более мелким — менее. Данный сайт построен на передовых, современных технологиях и не поддерживает Internet Explorer 6-ой и 7-ой версии. Есть версия Draw.io, которая устанавливается на компьютер.

Майндмэп поможет не забыть про все важные дела и распланировать день, неделю или даже год. В майндмэп можно расписывать рабочие задачи, учебные планы, важные встречи и повседневные дела. Воронка продаж — это путь, который проходит потребитель от знакомства с товаром или услугой до момента покупки или заключения сделки. Ментальная карта помогает пошагово прописать весь этот путь.

С их помощью можно составить расписание, распределить зоны ответственности при работе над проектом, не упустить мелкие детали. Интеллект-карты прекрасно подходят для работы над проектами любого масштаба. Например, мы в SendPulse используем майндмэпы для проектирования автоматических цепочек писем. В бесплатной версии программы можно создать 3 доски и сделать резервную копию майнд-карт из Miro. Чтобы создавать бесконечное количество досок и редактировать их с другими пользователями, нужно купить один из платных тарифов от 729 рублей в месяц. За 624 рубля пользователи составляют неограниченное число майнд-карт, но не могу делиться пространствами с другими членами команды.

Запуск нового продукта на рынок — сложная и многоэтапная процедура, как и внедрение нового проекта. Чтобы не упустить ни одной детали и грамотно распланировать все этапы запуска, можно нарисовать подробную ментальную карту. Их можно применять к рабочим задачам и повседневным делам, поэтому они пригодятся не только специалистам разных профессий, но и студентам, родителям и домохозяйкам. Вот лишь несколько примеров того, зачем нужны майндмэпс. Майндмэп помогает полностью охватить проблему, запомнить информацию, т.е.

майндмэп это

Огромный плюс составления плана действий с помощью Mind map в том, что карта позволяет видеть картину в целом. С ее помощью можно выделить отправную точку, цель, и что для ее достижения нужно сделать. Карта помогает при выборе одного из нескольких направлений.

Это схема, определяющая взаимосвязи между центральным звеном (задачей) и ее составляющими (пути решения). Стоимость подписки начинается от $4.99 в месяц для одного пользователя. В эту цену входят дополнительные шаблоны и возможность экспортировать карты в файлы с форматами  png, pdf, doc. В платной версии также есть режим совместной работы. Можно добавлять новые элементы в проекты коллег, комментировать правки и обсуждать ход работы во встроенном в сервис чате.

Santa Claus Rally: What It Is and Means for Investors

what is santa rally

In this examination of the Santa Claus rally, we’ll discuss the origins of the rally, why it happens, and the history behind it. Most of those in attendance at the rally were supporting the more comprehensive ban. The late Yale Hirsch, an American investment guru, first used the phrase in 1972, having chronicled the performance of the S&P 500 index between 1950 and 1971.

How Does A Santa Claus Rally Work?

This time of year, optimism can be contagious, leading many to buy stocks in anticipation of a favorable market trend. If you’ve experienced the thrill of holiday shopping, you know how that excitement can translate to your investment decisions. When optimism takes the wheel, it often results in a snowball effect, propelling stock prices higher as more investors hop on the bandwagon. The Santa Claus Rally isn’t just a seasonal curiosity—it’s a testament to how investor psychology, tax strategies, and market dynamics can align to create profitable opportunities. By understanding its patterns and incorporating tools like cycle analysis, traders can capitalize on this annual phenomenon with confidence. Whether you’re positioning for gains or protecting your portfolio, staying informed is key to making the most of this rally and the broader market trends it signals.

Whether one believes in the Santa Rally or not, it is undeniable that the holiday season has a unique influence on the stock market. Being aware of this phenomenon and adopting a prudent approach can help investors make more informed decisions and navigate the market with greater confidence. This rally is often characterized by a surge in market activity and a general sense of positivity and optimism among investors. The Santa Claus Rally refers to the stock market’s tendency to rise during the final five trading days of December and the first two trading days of January. This period often sees positive momentum, with stocks historically delivering higher-than-average returns compared to other times of the year. Several theories try to explain the Santa Claus rally, including investor optimism fueled by the holiday spirit, increased holiday shopping, and the investing of holiday bonuses.

It’s worth noting that in the week leading up to Christmas Day, there appears to be no evidence for or against a positive effect, though some analysts think that value stocks outperform growth stocks in this week. There are various calendar curiosities to consider when trading — for example, ‘sell in May and go away’ — or in other words, selling out of the markets during the summer. Then there’s the ‘October effect,’ where traders think the markets tend to sell-off during the month.

what is santa rally

Historical Trends Of The Santa Claus Rally

  • With a $10 investment minimum, diversifying your portfolio has never been easier.
  • Contradicting theories further add to the controversies surrounding the Santa Rally phenomenon.
  • A few weeks ago the US markets began to revive, driven by the view that inflation was retreating, and interest rate rises could be more limited than forecast.
  • Money Instructor® provides comprehensive resources that empower young people and adults with practical knowledge and skills in money management, investing, business, and the economy.
  • Suppose December approached and the holiday season unfolded, the stock market began to take on the familiar hue of a Santa Claus Rally.
  • The Santa Rally remains a subject of interest and speculation in the investment community.

It’s intriguing to think that while you’re caught up in holiday shopping and family gatherings, investors might capitalize on this phenomenon. The Santa Claus Rally refers to a historical trend in the stock market where stock prices rise in will disney stock crash in 2021 the last week of December and the first couple of days in January. This period is often seen as a time for favorable market conditions, attributed to the holiday season and increased consumer spending. The Santa Rally remains a subject of interest and speculation in the investment community. While skeptics question its predictability and economic basis, others see it as an opportunity to capitalize on market trends during the festive season.

The Significance of the Santa Claus Rally

Wachtel used the Dow Jones Industrial Average (DJIA) to study the effect from 1927 to 1942. Using the week leading up to Dec. 24 over two decades, we find there is no tangible or reliable Santa Claus rally. Whether you count that time period or the week after Dec. 25 up to Jan. 2 of the new year, the returns are negligible, if slightly positive at ultimate guide to forex currency pairs +0.385%. For the average return of the week leading up to Christmas, the so-called Santa Claus rally, we calculated a +0.385% total return, with 13 winning weeks, five losing weeks, and two unchanged weeks. More important, the average winning week gave a +1.85% return, while the losing weeks averaged a -3.28% return, skewing the risk/reward ratio against the trade (being long S&P 500). The week before Christmas typically has normal to significant volume, compared with the week after Christmas, which is usually marked by generally sideways stock-price movement with small ranges.

Artificial turf opponents rally ahead of vote on controversial Santa Clara County ban

what is santa rally

Traders should be wary of market talk surrounding the notion forex surowce indeksy etf of a Santa Claus rally, and stay fixed on the current market environment. While we can expect Santa Claus to deliver presents on time, we can’t expect him to always deliver reliable stock-market gains. The second major question is whether the Santa Claus rally really even exists.

  • “Those chemicals of concern, some of them are known to harm wildlife, others are known to harm humans,” Hinton said of chemicals often found in artificial turf fields.
  • Since 1969, the monthly average Santa Claus rally gain on the S&P 500 has been 1.7%.
  • The pattern has held true since 1950, with the broad market index increasing an average of 1.3%.
  • While the Santa Claus Rally isn’t a guaranteed occurrence, being aware of its historical performance can help you better strategize for your investments during this festive period.
  • Hence, the equity traders witness a sudden surge in stock prices, creating a bullish position.

Again, looking at the historical performance of the S&P 500 over the last two decades, we conclude that it is nearly a toss-up between a tangible rally and a normal trading week. In 2018, the S&P 500 finished the month with a 6.6% gain after December 24, which were the last four trading days of the month. Although the index fell on Jan. 3 — the second day of the new year — December 24 proved to be the market bottom. Founded in 1993, The Motley Fool is a financial services company dedicated to making the world smarter, happier, and richer.

What Is The Santa Claus Rally?

Understanding and analyzing this impact is crucial for investors seeking to make informed decisions during this period. For example, according to data compiled by LPL Research and FactSet, the Santa Claus rally period in 1999 saw the S&P 500 drop 4% and the Dotcom bubble burst in 2000. Similarly, corresponding trading days in 2007 saw the S&P 500 drop 2.5%, and 2008 saw the Great Recession.

Today, the Santa Claus Rally rally begins as early as November 25 and lasts through the end of the year. During this modern-day version of the Santa Claus Rally, the average S&P 500 return is double at 2.6%. The Dow Jones Industrial Average has increased by 1.38% on average over the holiday season and has done so 79% of the time since 1950. Since 1950, the S&P 500 has traded up 78% of the time during the Santa rally period, on average gaining 1.32%, according to Dow Jones Market Data (see chart above).

Differences Between Raster and Vector Images Comparison Chart

Most creative software will be able to open and display both raster and vector images, and some may even include tools for working with both. However, there are dedicated programs that are best suited for creating and editing each type of image. Although raster and vector formats both produce digital images, these images vary drastically in resolution, visual style, file compatibility and their creation process. Each of these are important factors to consider when deciding whether a vector or raster image is right for your project.

There are a number of programs for making vector-based drawings. Out of all the software available, Adobe Illustrator is the most popular, and its popularity has led it to become the industry standard. Learn how to come up with your own poster design ideas and see the process of bringing your idea to life in an online image editing tool. The image below shows a comparison of how Vector and Raster images are created.

Raster vs. Vector: What’s the Difference?

If you require complex colors and flawless color blending like a painting, choose Raster graphics. The number of pixels or pixels per inch (PPI) or the dots per inch (DPI) decides the raster image’s resolution. The higher the value of PPI or DPI, the higher the resolution of the raster image. Vector programs, on the other hand, involve more of a learning curve — even for experienced designers. The process of placing points, connecting lines and combining shapes is far less intuitive than digital painting.

Just as Illustrator is the industry standard for vector graphics, Photoshop is the standard for raster images. Sketchbook Pro and Corel Painter are other common raster editors, and file formats for raters include JPG, PSD, BMP, PNG, GIF, and TIF, just to site the most common examples. Other popular programs include CorelDraw and Affinity Designer, and vector images can be both created and edited using these programs. The most common file formats for vector graphics are AI, CDR, and SVG, depending on which software you’re using to design vector images. Instead of relying on millions of tiny of pixels per inch, vector graphics use mathematical formulas to define shapes, lines, and curves. Imagine them like digital blueprints where each element is precisely defined.

How Do I Know if My Image is a Vector?

This is one of the main differences between raster and vector images. A vector image’s formulaic makeup keeps file sizes to a minimum in comparison to its raster counterparts. This comes in handy when there are restrictions to file sizes or image storage.

raster and vector image difference

While a vector image file has many advantages, there are compatibility issues when shared. You must have access to vector-based programs in order to edit the native files. They’re made of paths and curves dictated by mathematical formulas.

Creation and Editing Programs

So, if you are printing business cards or flyers, designing an e-invite, or working with a cute illustration, vector images will serve your purpose. Raster graphics, also called bitmap graphics, a type of digital image that uses tiny rectangular pixels, or picture elements, arranged in a grid formation to represent an image. Vector graphics allow creatives to build high-quality works of art, with clean lines and shapes that can be scaled to any size.

  • Fortunately, these technical terms have straightforward explanations.
  • When images are created in these programs, they are exported to either a vector or raster image file type.
  • Scanning is basically another form of photography, as scanners and cameras both capture a high level of detail in a similar way, using raster image formatting.
  • The process of placing points, connecting lines and combining shapes is far less intuitive than digital painting.

Shutterstock’s collection of images includes tons of scalable vector graphics and images available for download, like fonts, patterns, and illustrations. To view vector images exclusively, change the Image Type located under the search bar and select Vectors. Between the two, raster images are the most stylistically versatile. Raster programs can be used both for minimalist artwork, high resolution photographs/photorealistic illustrations and everything in between.

What is the meaning of raster image?

Here, lines, curves, and other elements are paths, whereas the formula is a vector. The formula tells the path how it is shaped, what color it is filled with, and what the borders are like. Since raster graphics are made up of square-shaped pixels, they’re best for displaying more detailed images and subtle gradations in colored pixels.

However, they are unsuitable for projects involving different software. Thus, raster images are useful when displaying or storing high-quality images. As the pixel number is fixed, if you try to rescale the raster image to fill a larger space, then the image gets pixelated and starts looking blurry. The way to know for sure if your image is a vector file is to open it with a vector-based program, like Adobe Illustrator, Inkscape, or Affinity Designer, and inspect it.

Vector vs raster: Which is right for you?

Vector image formats are file types specifically designed to store vector graphics. Unlike raster image formats that rely on pixels, vector formats use mathematical formulas and paths to define shapes, lines, and curves. This allows for several advantages, such as infinite scalability and smaller file sizes. A vector image is a type of digital image that’s created using mathematical equations instead of pixels. Vector images are created in specialized programs like Adobe Illustrator or Inkscape.

raster and vector image difference

The larger the image, the more disk space the image file will take up. We use algorithms that compress images to help reduce these file sizes. Image formats like jpeg and gif are common compressed image formats. Scaling down these images is easy but enlarging a bitmap makes it pixelated or simply blurred. Hence for images that need to scale to different sizes, we use vector graphics. Images are created on the platform using pixels, and hence Photoshop is widely used for working with digital photographs.

Vector graphics are great for simplistic, or geometrical images such as logos, icons, illustrations, graphs, and typography. Virtually all photographs are in raster format — it’s simply the best format for that type of image. Scanning is basically another form of photography, as scanners and cameras both capture a high raster and vector graphics level of detail in a similar way, using raster image formatting. Because they are capable of high degrees of detail but are dependent on resolution, raster images are best used for design projects with fixed sizes and collages of images. A raster image is any digital photograph or illustration made up of pixels.

raster and vector image difference

What Generative AI Reveals About the Human Mind

The Difference Between Generative AI And Traditional AI: An Easy Explanation For Anyone

What is Generative AI?

Similarly, images are transformed into various visual elements, also expressed as vectors. One caution is that these techniques can also encode the biases, racism, deception and puffery contained in the training data. Generative AI can learn from existing artifacts to generate new, realistic artifacts (at scale) that reflect the characteristics of the training data but don’t repeat it. It can produce a variety of novel content, such as images, video, music, speech, text, software code and product designs.

What is Generative AI?

Generative AI is a type of machine learning, which, at its core, works by training software models to make predictions based on data without the need for explicit programming. Zero- and few-shot learning dramatically lower the time it takes to build an AI solution, since minimal data gathering is required to get a result. But as powerful as zero- and few-shot learning are, they come with a few limitations. First, many generative models are sensitive to how their instructions are formatted, which has inspired a new AI discipline known as prompt-engineering. A good instruction prompt will deliver the desired results in one or two tries, but this often comes down to placing colons and carriage returns in the right place.

I. Understanding Generative AI:

Transformers, introduced by Google in 2017 in a landmark paper “Attention Is All You Need,” combined the encoder-decoder architecture with a text-processing mechanism called attention to change how language models were trained. An encoder converts raw unannotated text into representations known as embeddings; the decoder takes these embeddings together with previous outputs of the model, and successively predicts each word in a sentence. This ability to generate novel data ignited a rapid-fire succession of new technologies, from generative adversarial networks (GANs) to diffusion models, capable of producing ever more realistic — but fake — images. Generative AI refers to deep-learning models that can generate high-quality text, images, and other content based on the data they were trained on. Generative AI models use neural networks to identify the patterns and structures within existing data to generate new and original content. Foremost are AI foundation models, which are trained on a broad set of unlabeled data that can be used for different tasks, with additional fine-tuning.

What is Generative AI?

Other generative AI models can produce code, video, audio, or business simulations. The next generation of text-based machine learning models rely on what’s known as self-supervised learning. This type of training involves feeding a model a massive amount of text so it becomes able to generate predictions.

Code

By iteratively refining their output, these models learn to generate new data samples that resemble samples in a training dataset, and have been used to create realistic-looking images. A diffusion model is at the heart of the text-to-image generation system Stable Diffusion. Generative AI models combine various AI algorithms to represent and process content.

  • Transformer-based models are trained on large sets of data to understand the relationships between sequential information, such as words and sentences.
  • But the study also found that, like all large language models, Gemini Pro particularly struggles with math problems involving several digits, and users have found plenty of examples of bad reasoning and mistakes.
  • Generative AI and large language models have been progressing at a dizzying pace, with new models, architectures, and innovations appearing almost daily.
  • GANs generally involve two neural networks.- The Generator and The Discriminator.
  • These include generative adversarial networks (GANs), transformers, and Variational AutoEncoders (VAEs).

These early implementations used a rules-based approach that broke easily due to a limited vocabulary, lack of context and overreliance on patterns, among other shortcomings. Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect. That said, the impact of generative AI on businesses, individuals and society as a whole hinges on how we address the risks it presents.

Putting the ‘art’ in artificial intelligence

I’m a philosopher and cognitive scientist who has spent their entire career trying to understand how the human mind works. Because the Gemini models are multimodal, they can in theory perform a range of tasks, from transcribing speech to captioning images and videos to generating artwork. Few of these capabilities have reached the product stage yet (more on that later), but Google’s promising all of them — and more — at some point in the not-too-distant future. A deepfake is a type of video or audio content created with artificial intelligence that depicts false events that are increasingly harder to discern as fake, thanks to generative AI platforms like Midjourney 5.1 and OpenAI’s DALL-E 2. Advances in artificial intelligence have also created a cottage industry for online scams using the technology.

What is Generative AI?

The main difference between traditional AI and generative AI lies in their capabilities and application. Traditional AI systems are primarily used to analyze data and make predictions, while generative AI goes a step further by creating new data similar to its training data. Ultimately, it’s critical that generative AI technologies are responsible and compliant by design, and that models and applications do not create unacceptable business risks. When AI is designed and put into practice within an ethical framework, it creates a foundation for trust with consumers, the workforce and society as a whole. The rise of generative AI is largely due to the fact that people can use natural language to prompt AI now, so the use cases for it have multiplied.

This has implications for a wide variety of industries, from IT and software organizations that can benefit from the instantaneous, largely correct code generated by AI models to organizations in need of marketing copy. In short, any organization that needs to produce clear written materials potentially stands to benefit. Organizations can also use generative AI to create more technical materials, such as higher-resolution versions of medical images.

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This means that we exist in a world where some of our brain’s predictions matter in a very special way. They matter because they enable us to continue to exist as the embodied, energy metabolizing, beings that we are. We humans also benefit hugely from collective practices of culture, science, and art, allowing us to share our knowledge and to probe and test our own best models of ourselves and our worlds. According to much contemporary theorizing, the human brain has learnt a model to predict certain kinds of data, too. But in this case the data to be predicted are the various barrages of sensory information registered by sensors in our eyes, ears, and other perceptual organs.

  • They are commonly used for text-to-image generation and neural style transfer.[40] Datasets include LAION-5B and others (See List of datasets in computer vision and image processing).
  • In a short book on the topic, the late Princeton philosopher Harry Frankfurt defined bullshit specifically as speech intended to persuade without regard to the truth.
  • Google, proving once again that it lacks a knack for branding, didn’t make it clear from the outset that Gemini is separate and distinct from Bard.
  • And while spreading propaganda is bad enough, there are also outright criminal uses – including attempts to extort money by staging hoax kidnappings using cloned voices and fraudulently scamming money by posing as a company CEO.
  • ChatGPT can produce what one commentator called a “solid A-” essay comparing theories of nationalism from Benedict Anderson and Ernest Gellner—in ten seconds.

New machine learning techniques developed in the past decade, including the aforementioned generative adversarial networks and transformers, have set the stage for the recent remarkable advances in AI-generated content. Generative AI models use a complex computing process known as deep learning to analyze common patterns and arrangements in large sets of data and then use this information to create new, convincing outputs. The models do this by incorporating machine learning techniques known as neural networks, which are loosely inspired by the way the human brain processes and interprets information and then learns from it over time. Generative AI models use neural networks to identify patterns in existing data to generate new content. Trained on unsupervised and semi-supervised learning approaches, organizations can create foundation models from large, unlabeled data sets, essentially forming a base for AI systems to perform tasks [1]. Whether it’s creating art, composing music, writing content, or designing products.

To learn more about what artificial intelligence is and isn’t, check out our comprehensive AI cheat sheet. Both relate to the field of artificial intelligence, but the former is a subtype of the latter. That’s the idea behind DreamGF, a platform that uses generative AI to create virtual girlfriends. That’s right, users can create their dream woman, including physical traits such as hair length, ethnicity, age, and breast size. As for her personality, users can select from a (notably smaller) number of descriptors such as „nympho,“ „dominatrix,“ or „nurse.“ Users can chat with their “girlfriend” via text and ask her to send nude pics. A DreamBF version is in the works for those who want to create their dream AI boyfriend.

Scientists and engineers have used several approaches to create generative AI applications. Prominent models include generative adversarial networks, or GANs; variational autoencoders, or VAEs; diffusion models; and transformer-based models. Generative AI represents a revolutionary leap forward in human-machine collaboration. By training models to generate original content, this technology transforms the creative landscape, opening up endless possibilities for artists, musicians, designers, and writers. With its wide-ranging applications and potential to reshape industries, Generative AI is poised to redefine the boundaries of human creativity and innovation.

One Google engineer was even fired after publicly declaring the company’s generative AI app, Language Models for Dialog Applications (LaMDA), was sentient. OpenAI, an AI research and deployment company, took the core ideas behind transformers to train its version, dubbed Generative Pre-trained Transformer, or GPT. Observers have noted that GPT is the same acronym used to describe general-purpose technologies such as the steam engine, electricity and computing. Most would agree that GPT and other transformer implementations are already living up to their name as researchers discover ways to apply them to industry, science, commerce, construction and medicine. A generative AI system is constructed by applying unsupervised or self-supervised machine learning to a data set.

What is Generative AI?

Likewise, striking a balance between automation and human involvement will be important if we hope to leverage the full potential of generative AI while mitigating any potential negative consequences. VAEs leverage two networks to interpret and generate data — in this case, it’s an encoder and a decoder. The decoder then takes this compressed information and reconstructs it into something new that resembles the original data, but isn’t entirely the same. Humans might use untrue material created by generative AI in an uncritical and thoughtless way. And that could make it harder for people to know what is true and false in the world.

What is Generative AI?

The model then generated 5,000 helpful, easy-to-read summaries for potential car buyers, a task CarMax said would have taken its editorial team 11 years to complete. The power of these systems lies not only in their size, but also in the fact that they can be adapted quickly for a wide range of downstream tasks without needing task-specific training. In zero-shot learning, the model uses a general understanding of the relationship between different concepts to make predictions and does not use any specific examples. In-context learning builds on this capability, whereby a model can be prompted to generate novel responses on topics that it has not seen during training using examples within the prompt itself. In-context learning techniques include one-shot learning, which is a technique where the model is primed to make predictions with a single example.

Exploring The Future: 5 Cutting-Edge Generative AI Trends In 2024 – Forbes

Exploring The Future: 5 Cutting-Edge Generative AI Trends In 2024.

Posted: Tue, 02 Jan 2024 05:21:47 GMT [source]

To realize quick returns, organizations can easily consume foundation models “off the shelf” through APIs. But to address their unique needs, companies will need to customize and fine-tune these models using their own data. Then the models can support specific tasks, such as powering customer service bots or generating product designs—thus maximizing efficiency and driving competitive advantage. The benefits of generative AI include faster product development, enhanced customer experience and improved employee productivity, but the specifics depend on the use case. End users should be realistic about the value they are looking to achieve, especially when using a service as is, which has major limitations. Generative AI creates artifacts that can be inaccurate or biased, making human validation essential and potentially limiting the time it saves workers.

Read more about What is Generative AI? here.