This paper presents a systematic literature review of published studies on AI-based automated speech therapy tools for persons with speech sound disorders (SSD). The COVID-19 pandemic has initiated the requirement for automated speech therapy tools for persons with SSD making speech therapy accessible and affordable. However, there are no guidelines for designing such automated tools and their required degree of automation compared to human experts. In this systematic review, we followed the PRISMA framework to address four research questions: 1) what types of SSD do AI-based automated speech therapy tools address, 2) what is the level of autonomy achieved by such tools, 3) what are the different modes of intervention, and 4) how effective are such tools in comparison with human experts. An extensive search was conducted on digital libraries to find research papers relevant to our study from 2007 to 2022. The results show that AI-based automated speech therapy tools for persons with SSD are increasingly gaining attention among researchers. Articulation disorders were the most frequently addressed SSD based on the reviewed papers. Further, our analysis shows that most researchers proposed fully automated tools without considering the role of other stakeholders. Our review indicates that mobile-based and gamified applications were the most frequent mode of intervention. The results further show that only a few studies compared the effectiveness of such tools compared to expert Speech-Language Pathologists (SLP). Our paper presents the state-of-the-art in the field, contributes significant insights based on the research questions, and provides suggestions for future research directions.

This paper explores the dual impact of digital banks and alternative lenders on financial inclusion and the regulatory challenges posed by their business models. It discusses the integration of digital platforms, machine learning (ML), and Large Language Models (LLMs) in enhancing financial services accessibility for underserved populations. Through a detailed analysis of operational frameworks and technological infrastructures, this research identifies key mechanisms that facilitate broader financial access and mitigate traditional barriers. Additionally, the paper addresses significant regulatory concerns involving data privacy, algorithmic bias, financial stability, and consumer protection. Employing a mixed-methods approach, which combines quantitative financial data analysis with qualitative insights from industry experts, this paper elucidates the complexities of leveraging digital technology to foster financial inclusivity. The findings underscore the necessity of evolving regulatory frameworks that harmonize innovation with comprehensive risk management. This paper concludes with policy recommendations for regulators, financial institutions, and technology providers, aiming to cultivate a more inclusive and stable financial ecosystem through prudent digital technology integration.

Stance detection, a key task in natural language processing, determines an author's viewpoint based on textual analysis. This study evaluates the evolution of stance detection methods, transitioning from early machine learning approaches to the groundbreaking BERT model, and eventually to modern Large Language Models (LLMs) such as ChatGPT, LLaMa-2, and Mistral-7B. While ChatGPT's closed-source nature and associated costs present challenges, the open-source models like LLaMa-2 and Mistral-7B offers an encouraging alternative. Initially, our research focused on fine-tuning ChatGPT, LLaMa-2, and Mistral-7B using several publicly available datasets. Subsequently, to provide a comprehensive comparison, we assess the performance of these models in zero-shot and few-shot learning scenarios. The results underscore the exceptional ability of LLMs in accurately detecting stance, with all tested models surpassing existing benchmarks. Notably, LLaMa-2 and Mistral-7B demonstrate remarkable efficiency and potential for stance detection, despite their smaller sizes compared to ChatGPT. This study emphasizes the potential of LLMs in stance detection and calls for more extensive research in this field.

Global conflicts and trouble spots have thrown the world into turmoil. Intelligence services have never been as necessary as they are today when it comes to providing political decision-makers with concrete, accurate, and up-to-date decision-making knowledge. This requires a common co-operation, a common working language and a common understanding of each other. The best way to create this "intelligence community" is through a harmonized intelligence education. In this paper, we show how joint intelligence education can succeed. We draw on the experience of Germany, where all intelligence services and the Bundeswehr are academically educated together in a single degree program that lays the foundations for a common working language. We also show how these experiences have been successfully transferred to a European level, namely to ICE, the Intelligence College in Europe. Our experience has shown that three aspects are particularly important: firstly, interdisciplinarity or better, transdisciplinarity, secondly, the integration of IT knowhow and thirdly, the development and learning of methodological skills. Using the example of the cyber intelligence module with a special focus on data-driven decision support, additionally with its many points of reference to numerous other academic modules, we show how the specific analytic methodology presented is embedded in our specific European teaching context.

The Lebanese militant group Hezbollah claimed responsibility for a cross-border drone and missile attack in northern Israel on Wednesday that the Israeli military said had injured 14 soldiers, six of them severely. It was one of the most damaging attacks in recent months by Hezbollah, Iran's most powerful regional proxy, in its continuing clashes with Israel. The attack came a day after Israel's targeted killing of two Hezbollah commanders as fears continue to grow of a broader conflict between Israel and Tehran, which mounted a wide aerial attack on Israel over the weekend. An internal Israeli army memo said an initial investigation found that Hezbollah had fired two anti-tank rockets at an Israeli Bedouin border village, Arab al-Aramshe, before dispatching an exploding drone. An Israeli military spokeswoman declined to comment on the memo.

Video captures the moment and aftermath of what appears to be a drone, allegedly of Ukrainian origin, striking Russian drone production facility. Russian officials claimed that only a worker's dormitory was hit. Three Russian missiles slammed into a downtown area of the northern Ukrainian city of Chernihiv on Wednesday, hitting an eight-floor apartment building and killing at least 14 people, authorities said. At least 61 people, including two children, were wounded in the morning attack, Ukrainian emergency services said. Chernihiv lies about 90 miles north of the capital, Kyiv, near the border with Russia and Belarus, and has a population of around 250,000 people.

The river in the small city of Penza suddenly turned green, residents said. The Ukrainian infantryman, call sign "Ray", said he quickly pulled on his gas mask after a Russian drone flying above his trench on the eastern front dropped a tear gas grenade. "It's like pepper spray, it makes your eyes tear up. It's not lethal, but it disturbs and knocks you out. It makes it very difficult to carry out your duties once you've inhaled it," he told Reuters of the attack he said he experienced in January.

Tehran, Iran – Israel has pledged to "exact a price" from Iran in response to missile and drone attacks launched by Tehran in retaliation to the deadly bombing of its consulate in Syria at the beginning of this month. Israel's war cabinet has met several times to debate a course of action to complement a diplomatic push against Iran since Saturday's unprecedented direct attacks on Israel, with Israeli army chief of staff Herzi Halevi saying a military response is certain. Iranian President Raisi threatened a "massive and harsh response" on Wednesday if Israel decides to launch a direct military assault on Iranian soil. So how effectively can Iran defend itself if such an attack occurs? For decades, Iran has increasingly insisted on relying on its local capabilities when it comes to its economy, but a similar push can also be seen in its military sector.

Almost 11 years after Boston Dynamics revealed the Atlas humanoid robot, it's finally being retired. The DARPA-funded robot was designed for search-and-rescue missions, but it rose to fame thanks to videos showing off its dance moves and--let's be honest--rudimentary parkour skills. Atlas is trotting off into the sunset with one final YouTube video, thankfully including plenty of bloopers -- which are the best parts. Boston Dynamics, of course, has more commercially successful robots in its lineup, including Spot. Meta's Oversight Board will rule on AI-generated sexual images Motorola's Edge 50 phone series includes a wood option You can get these reports delivered daily direct to your inbox.

Bellwether, a new group inside "X," the innovation lab that is part of Google's parent company Alphabet, has developed tech that can ingest photos taken at an angle by airplanes, compare them with satellite imagery and maps, and automatically identify locations, roads, buildings and other important infrastructure. Bellwether has been testing the tech with the National Guard, which will deploy it in time for the summer wildfire season, said Nirav Patel, a program manager with the Defense Innovation Unit (DIU), a Pentagon unit that helps the military integrate commercial technology and that helped organize the partnership.