Creators of a text-generating robot have released the tool to the public despite initial trepidation that it could be manipulated by bad actors. OpenAI - an Elon Musk-backed company that researches artificial intelligence- detailed its system, called GPT-2, in February, but stopped short of releasing it over concerns that it might be used to proliferate spam and fake news. The AI is capable of taking a snippet of text and extrapolating that small piece of information into a larger document. Above is an example of a prompt input by MailOnline. For instance, if fed a phony headline, the bot would be able to produce a fairly convincing fake news story based on the prompt.

Researchers have developed a deep learning model to accurately identify cancerous esophagus tissue on microscopy images instead of the high-cost, time-consuming manual annotation process used by pathologists. A research team at Dartmouth and Dartmouth-Hitchcock Norris Cotton Cancer Center tested their new machine learning approach for identifying cancerous and precancerous esophagus tissue on high-resolution microscopy images. Whole-slide images were collected from patients who underwent endoscopic esophagus and gastroesophageal junction mucosal biopsy, and an attention-based deep neural network framework was used to classify microscopy images. Results of the study were published on Wednesday in JAMA Network Open. "Previous methods for analyzing microscopy images were limited by bounding box annotations and unscalable heuristics," state the authors.

Deep learning, a recently described AI machine learning technique, when applied to image analysis, allows the algorithm to analyze data using multiple processing layers to extract different image features,1x1LeCun, Y., Bengio, Y., and Hinton, G. Deep learning. In ophthalmology, many groups have reported exceptional diagnostic performance using deep learning algorithms to detect various ocular conditions based on anterior segment topography (e.g., keratoconus),5x5Hwang, E.S., Perez-Straziota, C.E., Kim, S.W. et al. Distinguishing highly asymmetric keratoconus eyes using combined Scheimpflug and spectral-domain OCT analysis. Development and validation of a deep learning system for diabetic retinopathy and related eye diseases using retinal images from multiethnic populations with diabetes. Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Efficacy of a deep learning system for detecting glaucomatous optic neuropathy based on color fundus photographs.

The research lab OpenAI has released the full version of a text-generating AI system that experts warned could be used for malicious purposes. The institute originally announced the system, GPT-2, in February this year, but withheld the full version of the program out of fear it would be used to spread fake news, spam, and disinformation. Since then it's released smaller, less complex versions of GPT-2 and studied their reception. Others also replicated the work. In a blog post this week, OpenAI now says it's seen "no strong evidence of misuse" and has released the model in full.

The research lab OpenAI has released the full version of a text-generating AI system that experts warned could be used for malicious purposes. The institute originally announced the system, GPT-2, in February this year, but withheld the full version of the program out of fear it would be used to spread fake news, spam, and disinformation. Since then it's released smaller, less complex versions of GPT-2 and studied their reception. Others also replicated the work. In a blog post this week, OpenAI now says it's seen "no strong evidence of misuse" and has released the model in full.

AT&T Labs will be hosting the NYC WiMLDS community for an Intro to PyTorch event with Dr. Michela Paganini from Facebook AI Research! We would also like to thank Facebook for sponsoring this event. Links to Google Colab notebooks will be provided at the event. She joined Facebook in 2018 after earning her PhD in particle physics from Yale University under the supervision of Paul Tipton. Her work focuses on the empirical characterization of neural network dynamics using tools from theoretical and experimental physics.

In February, OpenAI announced that it had developed an algorithm that could write believable fake news and spam. Deciding that power was too dangerous to unleash, OpenAI planned a staged release so that it could offer pieces of the tech and analyze how it was used. Now, OpenAI says it has seen "no strong evidence of misuse," and this week, it published the full AI. The AI, GPT-2, was originally designed to answer questions, summarize stories and translate texts. But researchers came to fear that it could be used to pump out large volumes of misinformation.

In February, OpenAI announced that it had developed an algorithm that could write believable fake news and spam. Deciding that power was too dangerous to unleash, OpenAI planned a staged release so that it could offer pieces of the tech and analyze how it was used. Now, OpenAI says it has seen "no strong evidence of misuse," and this week, it published the full AI. The AI, GPT-2, was originally designed to answer questions, summarize stories and translate texts. But researchers came to fear that it could be used to pump out large volumes of misinformation.

Much of the focus on deep learning systems for vision has been in three areas: autonomous vehicles, facial recognition, and robotics. However, as with the many other areas of artificial intelligence (AI), vision will have a far wider impact on society than in those three areas. The logistics of relocation are heavily depending, no surprise, on what is being moved. Vision can be applied to that challenge in order to create more accurate estimates much faster than before. As a one news article points out, "about one in five Americans (23 percent) think that moving is more stressful than planning a wedding, according to new research. Twenty-seven percent think it's more stressful than a job interview, and more than one in 10 (13 percent) even go as far as to say it's more stressful than a week in jail."

PyTorch Datasets are objects that have a single job: to return a single datapoint on request. The exact form of the datapoint varies between tasks: it could be a single image, a slice of a time series, a tabular record or something else entirely. These are then passed on to a Dataloader which handles batching of datapoints and parallelism. Before PyTorch 1.2 the only available dataset class was the original "map-style" dataset. This simply requires the user to inherit from the torch.utils.data.Dataset class and implement the __len__ and __getitem__ methods, where __getitem__ receives an index which is mapped to some item in your dataset.