If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
LaMDA has been in the news after a Google engineer claimed it was sentient because its answers allegedly hint that it understands what it is. The engineer also suggested that LaMDA communicates that it has fears, much like a human does. What is LaMDA, and why are some under the impression that it can achieve consciousness? LaMDA is a language model. Fundamentally, it's a mathematical function (or a statistical tool) that describes a possible outcome related to predicting what the next words are in a sequence.
The societal impact of Artificial Intelligence (AI) dwarfs its technological impact. Already, we see AI everywhere in our daily lives; we see it in our grocery shopping app, our entertainment streaming lists, social media feeds, our dating lives, and the list goes on. The use of AI has become so naturally intertwined with our lives that we often forget to think about the future. We should ask ourselves the question of how we can unlock AI's full potential while keeping its risks at a minimum. And to investigate this question, we need to work together.
Anja Kaspersen and Wendell Wallach are senior fellows at Carnegie Council for Ethics in International Affairs. In November 2021, they published an article that changed the AI ethics conversation: Why Are We Failing at the Ethics of AI? Six months later, the questions the article raised are no closer to resolution. This article was a don't-hold-your-punches review on the state of AI ethics, with which I am in almost complete agreement. If we want to advance the AI conversation, this is still a good place to start. I've quoted a portion of their article, with my comments interspersed: While it is clear that AI systems offer opportunities across various areas of life, what amounts to a responsible perspective on their ethics and governance is yet to be realized.
It's the dream: Find a smoldering someone on a dating app, match with them, and quickly launch into a conversation filled with subtle compliments, definitive date night plans, and witty repartee. According to research conducted by Preply, -- a language learning app and platform, – more than 70 percent of dating app users surveyed said it's possible to engage in meaningful conversation, and even fall in love with someone, before ever meeting in person (having only spoken on an app). The challenge, of course, is getting there, shifting from the notification that "It's A Match!" into dialogue worthy of a Shonda Rhimes production. It's a daunting task, so we brought in the pros: rom-com authors. Mashable spoke with several -- all with books jam-packed with quippy dialogue out this spring and summer -- to get their expert takes on how to write witty banter.
Tragedy befalls a young samurai, Hiroki, and his village; in the aftermath, his duty toward his love and community are tested. The storytelling is saved partially by well-written and acted dialogue, all in Japanese. While the premise and story beats are predictable, the panache and drama of each line reading keeps it interesting. The team used a Japanese consultant to make sure the dialogue was historically accurate. It also helps to have an easy-to-hate villain in the demonic Kagerou, who cuts an imposing figure, looming over our hero's life.
Characters in games and other digital experiences are fairly stable and work from a series of lines and responses written long ago. But the future of the game can be more responsive, more productive, and of course AI-driven. InworldAI is trying to do this with a new beta tool that allows developers to create rich, interactive characters, as they are called other AIs. Over the past year, Inworld has claimed to be able to quickly create NPCs and similar characters with a few words of explanation and a rotating dial. Once created, it quickly becomes deeper and more interesting. Currently, these claims have obvious limitations.
Characters in games and other digital experiences tend to be rather static, working from a set of lines and responses written long ago. But the future of games could be more responsive, generative, and of course AI-powered -- something Inworld AI is attempting to enable with a newly available beta tool that lets developers create a rich, interactive characters as simply as they might tell another AI to draw a bird. Inworld's claims, which it has been putting about over the last year, are that it is able to quickly create NPCs and such like characters with just a few sentences of description and twiddled dials, and that once created they will instantly be deeper and more interesting to interact with than ordinary scripted characters. Now, there are obvious limitations to these claims -- you couldn't, for example, outdo the cryptic utterances of characters in Elden Ring, since those are highly crafted scripts intended to be encountered in a specific way. But what about the lady who runs the weapon shop in a fantasy world?
AI (artificial intelligence) technology has made tremendous progress in recent years. It is now possible to assess its capacity to perform specific tasks such as generating text, images, and sound. Now, what if we go even further with more complicated tests, like evaluating a job, for example, or more particularly, evaluating an AI system on its ability to do SEO? Below, we will test Generative Pre-trained Transformer 3 (GPT-3) created by OpenAI. Let's keep in mind that an AI system will mimic the data on which it is trained. SEO has been built alongside search engine progression, and everything is well documented in blogs, books, and interviews.
Language is the mark of humanity and cognizance, and conversation or dialogue is the most fundamental and a distinctive field of language. As we use more natural interfaces with technology, like language, our relationship is shifting to one where we increasingly humanize them. The simplest kinds of dialogue systems are chatbots, systems that can carry on extended conversations with the goal of mimicking the unstructured conversations or'chats' characteristic of informal human2human (H2H) interaction. Conversational AI expands the scope of today's chatbots from stiff preset replies to one that can take astute & pliant actions. Conversational AI learns to allow humans and computers to talk and work together in a more natural way.
We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (i.e., SAMSum and MediaSum) and 112k+ annotated summaries in different target languages. Based on the proposed ClidSum, we introduce two benchmark settings for supervised and semi-supervised scenarios, respectively. We then build various baseline systems in different paradigms (pipeline and end-to-end) and conduct extensive experiments on ClidSum to provide deeper analyses. Furthermore, we propose mDialBART which extends mBART-50 (a multi-lingual BART) via further pre-training. The multiple objectives used in the further pre-training stage help the pre-trained model capture the structural characteristics as well as important content in dialogues and the transformation from source to the target language. Experimental results show the superiority of mDialBART, as an end-to-end model, outperforms strong pipeline models on ClidSum. Finally, we discuss specific challenges that current approaches faced with this task and give multiple promising directions for future research. We have released the dataset and code at https://github.com/krystalan/ClidSum.