Midjourney is one of the leading drivers of the emerging technology of using artificial intelligence (AI) to create visual imagery from text prompts. The San Francisco-based startup recently made news as the engine behind the artwork that won an award in a Colorado state fair competition, and that's unlikely to be the last complicated issue that AI art will face in the coming years. Midjourney differentiates from others in the space by emphasizing the painterly aesthetics in the images it produces. The platform is not trying to create photorealistic images that can be mistaken for photographs, and CEO David Holz says he is personally very uneasy with the uncanny quality of deepfakes and other work that simulates reality too closely. Instead, Holz says Midjourney is designed to unlock the creativity of ordinary people by giving them tools to make beautiful pictures just by describing them.

The outlier, however, for ChatGPT is Appendix F, based on the prompt to generate variants on poetry dedicated to Turing. In this instance, the generated content bypassed Open AI's detector with high confidence as real (99.98%). In their original report [24], the authors found "detection rates of ~95% for detecting 1.5B GPT-2-generated text" and noted that "We believe this is not high enough accuracy for standalone detection and needs to be paired with metadata-based approaches, human judgment, and public education to be more effective." Like the evolution of ever larger language models (>100 billion), refinements also have built-in heuristics or guardrails for model execution. The Instruct-series of GPT-3 demonstrated the ability to answer questions directly without conversational meanderings. The ChatGPT includes longer-term conversational memory, such that the API can track the dialog even with leaps of narration that single API calls could not span. One can test dialogs with impersonal pronouns like "it" carrying forward in the conversation with context to previous API calls in a single session-one easily grasped example for ChatGPT's API memory as both powerful and expensive to encode for more extended conversations. As Turing himself posed the human capacity to list memories [1]: "Actual human computers really remember what they have to do Constructing instruction tables is usually described as'programming.'"

Feature transformation aims to extract a good representation (feature) space by mathematically transforming existing features. It is crucial to address the curse of dimensionality, enhance model generalization, overcome data sparsity, and expand the availability of classic models. Current research focuses on domain knowledge-based feature engineering or learning latent representations; nevertheless, these methods are not entirely automated and cannot produce a traceable and optimal representation space. When rebuilding a feature space for a machine learning task, can these limitations be addressed concurrently? In this extension study, we present a self-optimizing framework for feature transformation. To achieve a better performance, we improved the preliminary work by (1) obtaining an advanced state representation for enabling reinforced agents to comprehend the current feature set better; and (2) resolving Q-value overestimation in reinforced agents for learning unbiased and effective policies. Finally, to make experiments more convincing than the preliminary work, we conclude by adding the outlier detection task with five datasets, evaluating various state representation approaches, and comparing different training strategies. Extensive experiments and case studies show that our work is more effective and superior.

Um...are we travel writers all out of a job? If you've been following the recent advancements in the world of artificial intelligence, you'll know that there are unbelievable strides being made regarding the creation of original art. But there are also cutting-edge language models that can craft anything from original stories and college essays to writing jokes and crafting press releases. And for travelers, A.I. might even be able to help you plan your next trip–which has us travel writers a little bit nervous. But we wanted to see how far this technology has come, so we decided to put it to the test by conducting an interview with the ChatGPT A.I. engine to find out some of the best things to do in the coming year and hear about the travel space in general.

What is the best way to handle a high school teacher who just seems to--no matter what my child does--view her as a B student? It's her French class, and the class has many exams that are subjective. For instance, rubrics for oral presentations and written work differentiates between A's and B's by work being "very organized" and "organized," or "often uses complex sentences" and just "uses complex sentences." My child asks for feedback on her work, and she's (noticeably to the teacher) making an effort in class. The feedback she gets is as elusive as the rubrics--not very detailed, and it's not clear how to do "more" of what the teacher describes, since my child is already doing it. My child has always been a straight-A student, and she's incredibly stressed by this class, which she's currently getting a B in.

Rep. Brian Fitzpatrick, R-Pa., on U.S. aid delivered to Ukraine. EXCLUSIVE: The snow was piling up and blizzard-like conditions were mounting as Anastasiya Koval, an American Ukrainian, crossed into the recently liberated city of Kharkiv in early December while on a humanitarian mission to deliver aid to the front lines. "I didn't realize how massive the city was. It was my first time there," she described in an interview with Fox News Digital. "What really impacted me was when we finally crossed the bridge where the Russian soldiers had entered the city."

When evaluating the most significant innovations of any calendar year, it's often a struggle to decide among a handful of equally worthy contenders. Over the last 12 months, one category of technology has made headlines so often and has impacted society so significantly, there is no question that 2022 will be remembered as the year that Generative AI stunned the world. I don't just mean stunned the general public. Even lifelong technologists and AI researchers like myself were genuinely surprised by the speed and impact of recent advancements. So, what is Generative AI? It's a branch of artificial intelligence that enables computers quickly and convincingly to create original content ranging from images and artwork to poetry, music, text, video, dialog, and even computer code.

Generations of computing professionals may remember Frederick P. Brooks, Jr., as the author of the seminal text on system engineering, The Mythical Man-Month: Essays on Software Engineeringa and his essays such as No Silver Bullet--Essence and Accident in Software Engineering.b Those who worked with Brooks, winner of the 1999 ACM A.M. Turing Award "for landmark contributions to computer architecture, operating systems, and software engineering," may also remember him as the lead designer of IBM's System/360, as an innovator in graphics and virtual reality, and as the founder of the University of North Carolina's computer science department. Brooks was born on April 19, 1931, in Greenville, North Carolina. He received his A.B. in Physics from Duke University in 1953. As a freshman, he saw an article in the January 23, 1950 issue of Time Magazine entitled "The Thinking Machine" that sparked his interest in computing.

Sentence summarization shortens given texts while maintaining core contents of the texts. Unsupervised approaches have been studied to summarize texts without human-written summaries. However, recent unsupervised models are extractive, which remove words from texts and thus they are less flexible than abstractive summarization. In this work, we devise an abstractive model based on reinforcement learning without ground-truth summaries. We formulate the unsupervised summarization based on the Markov decision process with rewards representing the summary quality. To further enhance the summary quality, we develop a multi-summary learning mechanism that generates multiple summaries with varying lengths for a given text, while making the summaries mutually enhance each other. Experimental results show that the proposed model substantially outperforms both abstractive and extractive models, yet frequently generating new words not contained in input texts.

'I am a Machine, With no Soul or Heart': An Interview With Artificial Intelligence We asked OpenAI's human-like AI chatbot – ChatGPT – a little bit about itself, as well as a panel of profound questions; could delving into the mind of a computer provide insight undiscovered by humans so far?