The use of deep learning methods in scientific computing represents a potential paradigm shift in engineering problem solving. One of the most prominent developments is Physics-Informed Neural Networks (PINNs), in which neural networks are trained to satisfy partial differential equations (PDEs). While this method shows promise, the standard version has been shown to struggle in accurately predicting the dynamic behavior of time-dependent problems. To address this challenge, methods have been proposed that decompose the time domain into multiple segments, employing a distinct neural network in each segment and directly incorporating continuity between them in the loss function of the minimization problem. In this work we introduce a method to exactly enforce continuity between successive time segments via a solution ansatz. This hard constrained sequential PINN (HCS-PINN) method is simple to implement and eliminates the need for any loss terms associated with temporal continuity. The method is tested for a number of benchmark problems involving both linear and non-linear PDEs. Examples include various first order time dependent problems in which traditional PINNs struggle, namely advection, Allen-Cahn, and Korteweg-de Vries equations. Furthermore, second and third order time-dependent problems are demonstrated via wave and Jerky dynamics examples, respectively. Notably, the Jerky dynamics problem is chaotic, making the problem especially sensitive to temporal accuracy. The numerical experiments conducted with the proposed method demonstrated superior convergence and accuracy over both traditional PINNs and the soft-constrained counterparts.

A significant hurdle in the noisy intermediate-scale quantum (NISQ) era is identifying functional quantum circuits. These circuits must also adhere to the constraints imposed by current quantum hardware limitations. Variational quantum algorithms (VQAs), a class of quantum-classical optimization algorithms, were developed to address these challenges in the currently available quantum devices. However, the overall performance of VQAs depends on the initialization strategy of the variational circuit, the structure of the circuit (also known as ansatz), and the configuration of the cost function. Focusing on the structure of the circuit, in this thesis, we improve the performance of VQAs by automating the search for an optimal structure for the variational circuits using reinforcement learning (RL). Within the thesis, the optimality of a circuit is determined by evaluating its depth, the overall count of gates and parameters, and its accuracy in solving the given problem. The task of automating the search for optimal quantum circuits is known as quantum architecture search (QAS). The majority of research in QAS is primarily focused on a noiseless scenario. Yet, the impact of noise on the QAS remains inadequately explored. In this thesis, we tackle the issue by introducing a tensor-based quantum circuit encoding, restrictions on environment dynamics to explore the search space of possible circuits efficiently, an episode halting scheme to steer the agent to find shorter circuits, a double deep Q-network (DDQN) with an $\epsilon$-greedy policy for better stability. The numerical experiments on noiseless and noisy quantum hardware show that in dealing with various VQAs, our RL-based QAS outperforms existing QAS. Meanwhile, the methods we propose in the thesis can be readily adapted to address a wide range of other VQAs.

The computer scientist and CEO who popularized the term'artificial general intelligence' (AGI) believes AI is verging on an exponential'intelligence explosion.' The PhD mathematician and futurist Ben Goertzel made the prediction while closing out a summit on AGI this month: 'It seems quite plausible we could get to human-level AGI within, let's say, the next three to eight years.' 'Once you get to human-level AGI,' Goertzel, sometimes called'father of AGI,' added, 'within a few years you could get a radically superhuman AGI.' While the futurist admitted that he'could be wrong,' he went on to predict that the only impediment to a runaway, ultra-advanced AI -- far more advanced than its human makers -- would be if the bot's'own conservatism' advised caution. Mathematician and futurist Ben Goertzel made the prediction while closing out a summit on AGI las week: 'we could get to human-level AGI within, let's say, the next three to eight years' Goertzel made his predictions during his closing remarks last week at the '2024 Beneficial AI Summit and Unconference,' partially sponsored by his own firm SingularityNET where he is CEO.

A Chinese software engineer has been arrested for allegedly stealing artificial intelligence technology from Google while secretly working for two Chinese companies. Linwei Ding, 38, also known as Leon Ding, faces four counts of theft of trade secrets, the US attorney general, Merrick Garland, said in a statement. Ding, who was arrested on Wednesday in Newark, California, allegedly transferred confidential information from Google's network to his personal account while secretly affiliated with Chinese-based companies in the AI industry. "The justice department will not tolerate the theft of artificial intelligence and other advanced technologies that could put our national security at risk," Garland said. "We will fiercely protect sensitive technologies developed in America from falling into the hands of those who should not have them."

An artificial intelligence engineer at Microsoft published a letter Wednesday alleging that the company's AI image generator lacks basic safeguards against creating violent and sexualized images. In the letter, engineer Shane Jones states that his repeated attempts to warn Microsoft management about the problems failed to result in any action. Jones said he sent the message to the Federal Trade Commission and Microsoft's board of directors. "Internally the company is well aware of systemic issues where the product is creating harmful images that could be offensive and inappropriate for consumers," Jones states in the letter, which he published on LinkedIn. He lists his title as "principal software engineering manager".

Since OpenAI released ChatGPT in November 2022, we have seen increased excitement about generative artificial intelligence (AI), coupled with concerns about its safety. Given this inflection point, we must pay renewed attention to its impact on the future of knowledge work carried out by professionals. This is because compared to earlier types of AI, generative AI gets closer to the core activities of professionals, namely giving advice to and treating clients. And yet, how and how fast professionals' work will change is not well understood. Instead of leaving the issue to be part of "unintended consequences,"3 this column argues that we can influence how generative AI will become embedded in the work we do as professionals. Professionals in a variety of fields--including medicine, audit, accounting, law, and data science--are essentially in the business of diagnosis and treatment, connecting the two via inference.

The tech giant said the lawsuit was near-sighted and akin to Hollywood's losing backlash against the VCR. In a motion to dismiss part of the lawsuit filed Monday, Microsoft, which was sued in December alongside ChatGPT-maker OpenAI, scoffed at the newspaper's claim that Times content receives "particular emphasis" and that tech companies "seek to free-ride on the Times's massive investment in its journalism". But in its response, Microsoft said the lawsuit was akin to Hollywood's resistance to the VCR that consumers used to record TV shows and which the entertainment business in the late 1970s feared would destroy its economic model. "'The VCR is to the American film producer and the American public as the Boston strangler is to the woman home alone,'" Microsoft said in its response, quoting from congressional testimony delivered by Jack Valenti, then head of the motion picture association of America, in 1982. In this case, Microsoft said, the Times is attempting to use "its might and its megaphone to challenge the latest profound technological advance: the Large Language Model."

Microsoft engineer Shane Jones raised concerns about the safety of OpenAI's DALL-E 3 back in January, suggesting the product has security vulnerabilities that make it easy to create violent or sexually explicit images. He also alleged that Microsoft's legal team blocked his attempts to alert the public to the issue. Now, he has taken his complaint directly to the FTC, as reported by CNBC. "I have repeatedly urged Microsoft to remove Copilot Designer from public use until better safeguards could be put in place," Jones wrote in a letter to FTC Chair Lina Khan. He noted that Microsoft "refused that recommendation" so now he's asking the company to add disclosures to the product to alert consumers to the alleged danger. Jones also wants the company to change the rating on the app to make sure it's only for adult audiences.

ROUGH'ROAD': The Jake Gyllenhaal-starring "Road House" remake is facing two major hurdles ahead of its release. 'IDEOLOGICAL ECHO CHAMBER': The controversy surrounding the artificial intelligence chatbot Gemini is reigniting concerns about political bias at Google, a company that has repeatedly been accused of favoring Democrats and fostering a culture of progressive workers. CAPITALIZING ON CONSUMERS: Elon Musk is suing ChatGPT-maker OpenAI and its chief executive Sam Altman, among others, saying they had abandoned the company's original founding mission to develop open-source artificial general intelligence technology for the benefit of humanity over profits. CREEPY COMPANION: Have you ever wished for a robot friend who can keep you company, teach you new skills and inspire you to explore the wonders of technology? If so, you might want to check out Doly, the latest creation from Limibit, a technology startup based in Ontario, Canada.

Elon Musk supported making OpenAI a for-profit company, the ChatGPT maker said, attacking a lawsuit from the wealthy investor who has accused the artificial intelligence business of betraying its founding goal to benefit humanity as it pursued profits instead. In its first response since the Tesla CEO sued last week, OpenAI vowed to get the claim thrown out and released emails from Musk, escalating the feud between the San Francisco-based company and the billionaire that bankrolled its creation years ago. "The mission of OpenAI is to ensure AGI benefits all of humanity, which means both building safe and beneficial AGI and helping create broadly distributed benefits," OpenAI said in a blog post late Tuesday from five company executives and computer scientists, including CEO Sam Altman. "We intend to move to dismiss all of Elon's claims." AGI refers to artificial general intelligence, which are general purpose AI systems that can perform just as well as -- or even better than -- humans in a wide variety of tasks.