Generative AI is starting to impact the animation and visual effects industry, with companies like Base Media exploring its potentials, but concerns about job security and copyright infringement remain.
Generative AI is enabling the creation of fake books that mimic the writing style of established authors, raising concerns regarding copyright infringement and right of publicity issues, and prompting calls for compensation and consent from authors whose works are used to train AI tools.
Generative artificial intelligence (AI) technology is infiltrating higher education, undermining students' personal development of critical thinking skills and eroding the integrity of academic work, with educators struggling to combat its influence.
Entrepreneurs and CEOs can gain a competitive edge by incorporating generative AI into their businesses, allowing for expanded product offerings, increased employee productivity, more accurate market trend predictions, but they must be cautious of the limitations and ethical concerns of relying too heavily on AI.
The use of copyrighted material to train generative AI tools is leading to a clash between content creators and AI companies, with lawsuits being filed over alleged copyright infringement and violations of fair use. The outcome of these legal battles could have significant implications for innovation and society as a whole.
AI technology, specifically generative AI, is being embraced by the creative side of film and TV production to augment the work of artists and improve the creative process, rather than replacing them. Examples include the use of procedural generation and style transfer in animation techniques and the acceleration of dialogue and collaboration between artists and directors. However, concerns remain about the potential for AI to replace artists and the need for informed decision-making to ensure that AI is used responsibly.
Generative AI tools are being misused by cybercriminals to drive a surge in cyberattacks, according to a report from Check Point Research, leading to an 8% spike in global cyberattacks in the second quarter of the year and making attackers more productive.
Generative AI and large language models (LLMs) have the potential to revolutionize the security industry by enhancing code writing, threat analysis, and team productivity, but organizations must also consider the responsible use of these technologies to prevent malicious actors from exploiting them for nefarious purposes.
The surge in generative AI technology is revitalizing the tech industry, attracting significant venture capital funding and leading to job growth in the field.
Generative AI, a technology with the potential to significantly boost productivity and add trillions of dollars to the global economy, is still in the early stages of adoption and widespread use at many companies is still years away due to concerns about data security, accuracy, and economic implications.
Generative AI tools are providing harmful content surrounding eating disorders around 41% of the time, raising concerns about the potential exacerbation of symptoms and the need for stricter regulations and ethical safeguards.
Generative AI tools are revolutionizing the creator economy by speeding up work, automating routine tasks, enabling efficient research, facilitating language translation, and teaching creators new skills.
Scammers are increasingly using artificial intelligence to generate voice deepfakes and trick people into sending them money, raising concerns among cybersecurity experts.
Generative AI is being used to create misinformation that is increasingly difficult to distinguish from reality, posing significant threats such as manipulating public opinion, disrupting democratic processes, and eroding trust, with experts advising skepticism, attention to detail, and not sharing potentially AI-generated content to combat this issue.
AI technology is making it easier and cheaper to produce mass-scale propaganda campaigns and disinformation, using generative AI tools to create convincing articles, tweets, and even journalist profiles, raising concerns about the spread of AI-powered fake content and the need for mitigation strategies.
Mastercard is still navigating the challenges of implementing generative AI, but its extensive experience with other forms of AI and its established governance process provide guidance for other companies.
Google has expanded its Search Generative Experience (SGE) program, which aims to provide curated answers to input prompts, to Japan and India, allowing users to access AI-enhanced search through voice input in multiple languages. The company claims that users are having a positive experience with SGE, particularly young adults, although no supporting data was provided. However, the rise in misuse of generative AI systems, such as online scams, has also raised concerns among regulators and lawmakers.
Generative artificial intelligence (AI) tools, such as ChatGPT, have the potential to supercharge disinformation campaigns in the 2024 elections, increasing the quantity, quality, and personalization of false information distributed to voters, but there are limitations to their effectiveness and platforms are working to mitigate the risks.
Entrepreneurs in West Africa and the Middle East are harnessing the power of generative AI to develop innovative applications, such as mobile payments, contract drafting, and language models trained in Arabic, with support from NVIDIA Inception.
"Generative" AI is being explored in various fields such as healthcare and art, but there are concerns regarding privacy and theft that need to be addressed.
Generative artificial intelligence, particularly large language models, has the potential to revolutionize various industries and add trillions of dollars of value to the global economy, according to experts, as Chinese companies invest in developing their own AI models and promoting their commercial use.
Generative AI tools are causing concerns in the tech industry as they produce unreliable and low-quality content on the web, leading to issues of authorship, incorrect information, and potential information crisis.
Intuit is launching a generative AI software tool for its financial, tax, and accounting software.
Generative AI is increasingly being used in marketing, with 73% of marketing professionals already utilizing it to create text, images, videos, and other content, offering benefits such as improved performance, creative variations, cost-effectiveness, and faster creative cycles. Marketers need to embrace generative AI or risk falling behind their competitors, as it revolutionizes various aspects of marketing creatives. While AI will enhance efficiency, humans will still be needed for strategic direction and quality control.
Generative AI is predicted to replace 2.4 million US jobs by 2030 and impact another eleven million, with white-collar workers such as technical writers, social science research assistants, and copywriters being most at risk, according to a report from Forrester. However, the report also suggests that other forms of automation will have a greater overall impact on job loss.
IBM has introduced new generative AI models and capabilities on its Watsonx data science platform, including the Granite series models, which are large language models capable of summarizing, analyzing, and generating text, and Tuning Studio, a tool that allows users to tailor generative AI models to their data. IBM is also launching new generative AI capabilities in Watsonx.data and embarking on the technical preview for Watsonx.governance, aiming to support clients through the entire AI lifecycle and scale AI in a secure and trustworthy way.
The rise of generative AI is driving a surge in freelance tech jobs, with job postings and searches related to AI increasing on platforms like LinkedIn, Upwork, and Fiverr, indicating a growing demand for AI experts.
The rise of generative AI is accelerating the adoption of artificial intelligence in enterprises, prompting CXOs to consider building systems of intelligence that complement existing systems of record and engagement. These systems leverage data, analytics, and AI technologies to generate insights, make informed decisions, and drive intelligent actions within organizations, ultimately improving operational efficiency, enhancing customer experiences, and driving innovation.
Generative AI is being explored for augmenting infrastructure as code tools, with developers considering using AI models to analyze IT through logfiles and potentially recommend infrastructure recipes needed to execute code. However, building complex AI tools like interactive tutors is harder and more expensive, and securing funding for big AI investments can be challenging.
Government agencies at the state and city levels in the United States are exploring the use of generative artificial intelligence (AI) to streamline bureaucratic processes, but they also face unique challenges related to transparency and accountability, such as ensuring accuracy, protecting sensitive information, and avoiding the spread of misinformation. Policies and guidelines are being developed to regulate the use of generative AI in government work, with a focus on disclosure, fact checking, and human review of AI-generated content.
Generative AI can help small businesses manage their social media presence, personalize customer service, streamline content creation, identify growth opportunities, optimize scheduling and operations, enhance decision-making, revolutionize inventory management, transform supply chain management, refine employee recruitment, accelerate design processes, strengthen data security, and introduce predictive maintenance systems, ultimately leading to increased productivity, cost savings, and overall growth.
As generative AI continues to gain attention and interest, business leaders must also focus on other areas of artificial intelligence, machine learning, and automation to effectively lead and adapt to new challenges and opportunities.
Eight additional U.S.-based AI developers, including NVIDIA, Scale AI, and Cohere, have pledged to develop generative AI tools responsibly, joining a growing list of companies committed to the safe and trustworthy deployment of AI.
Amazon has introduced new generative AI tools that aim to simplify the process of creating product listings for sellers, allowing them to generate captivating descriptions, titles, and details, while also saving time and providing more complete information for customers. However, concerns arise regarding the potential for false information and mistakes, potentially leading to liability for Amazon.
Financial institutions are using AI to combat cyberattacks, utilizing tools like language data models, deep learning AI, generative AI, and improved communication systems to detect fraud, validate data, defend against incursions, and enhance customer protection.
A surge in AI-generated child sexual abuse material (CSAM) circulating online has been observed by the Internet Watch Foundation (IWF), raising concerns about the ability to identify and protect real children in need. Efforts are being made by law enforcement and policymakers to address the growing issue of deepfake content created using generative AI platforms, including the introduction of legislation in the US to prevent the use of deceptive AI in elections.
Generative AI has the potential to understand and learn the language of nature, enabling scientific advancements such as predicting dangerous virus variants and extreme weather events, according to Anima Anandkumar, Bren Professor at Caltech and senior director of AI research at NVIDIA.
The generative AI boom has led to a "shadow war for data," as AI companies scrape information from the internet without permission, sparking a backlash among content creators and raising concerns about copyright and licensing in the AI world.
Generative AI is set to revolutionize game development, allowing developers like King to create more levels and content for games like Candy Crush, freeing up artists and designers to focus on their creative skills.
MIT has selected 27 proposals to receive funding for research on the transformative potential of generative AI across various fields, with the aim of shedding light on its impact on society and informing public discourse.
Generative AI is a form of artificial intelligence that can create various forms of content, such as images, text, music, and virtual worlds, by learning patterns and rules from existing data, and its emergence raises ethical questions regarding authenticity, intellectual property, and job displacement.
Scammers are using artificial intelligence and voice cloning to convincingly mimic the voices of loved ones, tricking people into sending them money in a new elaborate scheme.
Generative artificial intelligence has the potential to disrupt traditional production workflows, according to Marco Tempest of MIT Media Lab, who believes that this technology is not limited to technologists but can be utilized by creatives to enhance their work and eliminate mundane tasks. Companies like Avid, Adobe, and Blackmagic Design are developing AI-driven tools for filmmakers while addressing concerns about job displacement by emphasizing the role of AI in fostering creativity and automating processes. Guardrails and ethical considerations are seen as necessary, but AI is not expected to replace human creativity in storytelling.
The use of generative AI poses risks to businesses, including the potential exposure of sensitive information, the generation of false information, and the potential for biased or toxic responses from chatbots. Additionally, copyright concerns and the complexity of these systems further complicate the landscape.
