Florida International University’s Moss Department of Construction Management is at the forefront of a revolution in the industry. They’re equipping students with the tools to leverage AI for increased efficiency and safety on construction sites.
Imagine generating blueprints with just a few specifications or having a watchful eye constantly monitoring a site for safety hazards. These are just a few ways AI is transforming construction. Students like Kaelan Dodd are already putting this knowledge to work. ‘An AI tool I tried at my job based on what I learned at FIU lets us create blueprints in seconds,’ Dodd said, impressed by the technology’s potential.
But FIU’s course goes beyond simply using AI. Professor Lufan Wang understands the importance of students not just using the technology but understanding it. By teaching them to code, she gives them a ‘translator’ to communicate with AI and provides valuable feedback to improve its capabilities. An approach like this one prepares students to not only navigate the constantly evolving world of AI but also shape its future applications in construction.
The benefits of AI extend far beyond efficiency. Construction is a field where safety is paramount, and AI can be a valuable ally. Imagine having a tireless AI assistant analyse thousands of construction site photos to identify potential hazards or sending an AI-powered robot into a dangerous situation to gather information. These are a few ways AI can minimise risk and potentially save lives. While AI won’t replace human construction managers entirely, it can take on the most dangerous tasks, allowing human expertise to focus on what it does best – guiding and overseeing complex projects.
Anthropic is launching a new program to fund the creation of new benchmarks for better assessing AI model performance and its impact. In its blog post, Anthropic stated that it will offer grants to third-party organisations developing improved methods for evaluating advanced AI model capabilities.
Urging the AI research community to develop more rigorous benchmarks that address societal and security implications, Anthropic advocated for revising existing methodologies through new tools, infrastructure, and methods. Highlighting how they aim to develop an early warning system to identify and assess risks, it specifically called for tests to evaluate a model’s ability to conduct cyberattacks, enhance weapons of mass destruction, and manipulate or deceive individuals.
Moreover, Anthropic also aims for its new program to support research into benchmarks and tasks that explore AI’s potential in scientific study, multilingual communication, bias mitigation, and self-censorship of toxicity. In addition to grants, researchers will have the chance to consult with the company’s domain experts. The company also expressed interest in potentially investing in or acquiring the most promising projects, offering various ‘funding options tailored to the needs and stage of each project’.
Why does this matter?
Benchmarks are the process of evaluating the quality of an AI system. The evaluation is typically a fixed process of assessing the capability of an AI model, usually in one area, while AI models like Anthropic’s Claude and Open AI’s ChatGPT are designed to perform a host of tasks. Thus, developing robust and reliable model evaluations is complex and is riddled with challenges. Anthropic’s initiative to support new AI benchmarks is commendable, with their stated objective of the program serving as a catalyst for progress towards a future where comprehensive AI evaluation is an industry-standard. However, given their own commercial interests, the initiative may raise trust concerns.
The UN General Assembly has adopted a resolution on AI capacity building, led by China. This non-binding resolution seeks to enhance developing countries’ AI capabilities through international cooperation and capacity-building initiatives. It also urges international organisations and financial institutions to support these efforts.
The resolution comes in the context of the ongoing technology rivalry between Beijing and Washington, as both nations strive to influence AI governance and portray each other as destabilising forces. Earlier this year, the US promoted a UN resolution advocating for ‘safe, secure, and trustworthy’ AI systems, gaining the support of over 110 countries, including China.
China’s resolution acknowledges the UN’s role in AI capacity-building and calls on Secretary-General Antonio Guterres to report on the unique challenges developing countries face and provide recommendations to address them.
Connecticut is spearheading efforts by developing what could be the nation’s first Citizens AI Academy. The free online resource aims to offer classes for learning basic AI skills and obtaining employment certificates.
Democratic Senator James Maroney of Connecticut emphasised the need for continuous learning in this rapidly evolving field. Determining the essential skills for an AI-driven world presents challenges due to the technology’s swift progression and varied expert opinions. Gregory LaBlanc from Berkeley Law School suggested that workers should focus on managing and utilising AI rather than understanding its technical intricacies to complement the capabilities of AI.
Several states, including Connecticut, California, Mississippi, and Maryland, have proposed legislation addressing AI in education. For instance, California is considering incorporating AI literacy into school curricula to ensure students understand AI principles, recognise its use, and appreciate its ethical implications. Connecticut’s AI Academy plans to offer certificates for career-related skills and provide foundational knowledge, from digital literacy to interacting with chatbots.
Despite the push for AI education, concerns about the digital divide persist. Senator Maroney highlighted the potential disadvantage for those needing more basic digital skills or access to technology. Marvin Venay of Bring Tech Home and Tesha Tramontano-Kelly of CfAL for Digital Inclusion stress the importance of affordable internet and devices as prerequisites for effective AI education. Ensuring these fundamentals is crucial for equipping individuals with the necessary tools to thrive in an AI-driven future.
Grammy Award-winning musician and producer Chance the Rapper is known for his innovative approach to music and fashion. Recently, he has teamed up with Meta for their Super Fan event, showcasing his interest in cutting-edge technology, particularly Meta AI. The collaboration highlights how AI transforms various aspects of his work, from engaging fans to creating music and fashion.
Chance has long been a pioneer in using digital platforms to connect with fans and distribute his music. With the advent of AI, he is now pushing the boundaries of creativity even further. He likens AI to the patchwork denim look he sported at the Meta event, describing it as an amalgamation of different design patterns. The comparison underscores his view of AI as a tool for combining diverse elements to create something unique.
The Meta AI suite, integrated into platforms like Instagram and Facebook, allows Chance to explore new artistic directions. He uses these tools to experiment with music production, generate unique soundscapes, and refine his musical style. Chance also finds inspiration on Instagram, drawing from various topics and incorporating these influences into his work.
Additionally, Chance sees potential in Meta’s new Ray-Ban Meta smart glasses, which offer responsive tech for human engagement and photography. By leveraging AI tools, he enhances his artistic process, engages more effectively with fans, and supports initiatives like the growth of women’s sports. As he prepares to release his new project, ‘Star Line Gallery,’ Chance the Rapper continues to inspire and innovate in the realms of music and fashion.
In the evolving landscape of marketing and advertising, the integration of generative AI presents both promise and challenges, as highlighted in a recent Forrester report. Key obstacles include a lack of AI expertise among agency employees and concerns over job obsolescence. Also, the human factor poses a significant hurdle that the industry must address urgently to fully harness the potential of genAI.
The potential economic impact of genAI on agencies is profound. Seen as a transformative force akin to the advent of smartphones, genAI promises to redefine creativity in marketing by combining data intelligence with human intuition. Agency leaders overwhelmingly recognise it as a disruptive technology, with 77% acknowledging its potential to fundamentally alter business operations. However, the fear of job displacement among employees remains palpable, exacerbated by recent industry disruptions and the rapid automation of white-collar roles.
To mitigate these concerns and fully embrace genAI, there is a pressing need for comprehensive AI literacy and training within agencies. While existing educational programmes and certifications provide a foundation, they are insufficient to meet the demands of integrating AI into everyday creative processes. Investment in reskilling and upskilling initiatives is crucial to empower agency employees to confidently navigate the AI-driven future of marketing and advertising.
Industry stakeholders, including agencies, technology partners, universities, and trade groups, must collaborate to establish robust training frameworks. In addition, a concerted effort will not only bolster agency capabilities in AI adoption but also ensure that creative workforce remains agile and competitive in an increasingly AI-centric landscape. By prioritising AI literacy and supporting continuous learning initiatives, agencies can position themselves at the forefront of innovation, delivering enhanced value to clients through AI-powered creativity.
SoftBank Group has launched a joint venture called ‘SB TEMPUS Corp.’ with Tempus AI, a leader in AI and precision medicine. The joint venture aims to provide precision medicine services in Japan by applying the expertise and technology that Tempus has accumulated in the US. That includes Tempus’ AI-enabled platform, which works to make diagnostics more intelligent and support healthcare providers in making more informed decisions. The goal is to provide personalised, data-driven therapies to patients, with the aim of helping them live longer and healthier lives.
A key focus of the joint venture will be collecting and analysing siloed and unstructured medical data, such as molecular, clinical, pathological, and medical imaging data. By leveraging AI to analyse this data, the joint venture aims to contribute to the advancement of pharmaceutical research, including clinical and drug discovery research and the proposal of treatment plans more suited to individual patients. That approach is expected to reduce side effects and enhance the effectiveness of medications, marking a significant step towards personalised medicine.
To help as many people suffering from cancer as possible, SB TEMPUS plans to establish collaborations with cancer genomic medicine hospitals and Japanese hospitals, medical facilities, pharmaceutical companies, biotech ventures, medical device companies, cancer insurance companies, and testing companies.
Why does it matter?
The collaborative network will support the provision of better diagnosis and treatment for patients, ensuring that they benefit from personalised, data-driven therapies. Also, the joint venture aligns with SoftBank’s corporate philosophy of ‘Information Revolution—Happiness for everyone.’
Amazon’s AWS, the leading global cloud computing provider, is intensifying efforts to draw the public sector into the realm of AI amidst fierce competition with Microsoft and Google in the generative AI domain. The initiative aims to demonstrate AI’s potential to enhance public services across health, security, and non-profit sectors, leveraging technologies like ChatGPT to streamline operations and improve outcomes.
Over two years, AWS has allocated a substantial $50 million fund to support public sector entities in exploring AI applications, offering cloud computing credits, training, and technical expertise to kickstart innovative projects. Currently serving thousands of government agencies, academic institutions, and nonprofits worldwide, AWS seeks to transition AI concepts into practical solutions that can effectively address public sector challenges.
Dave Levy, AWS’s vice president overseeing global public sector operations, highlighted the importance of moving from conceptualisation to implementation in public sector AI projects, underscoring the need for robust support to navigate complexities and achieve meaningful impacts. The push comes amid heightened competition as Microsoft and Google Cloud aggressively pursue public sector AI adoption, aiming to leverage vast datasets and AI capabilities to revolutionise service delivery and operational efficiency.
Amazon’s AWS remains committed to addressing challenges such as data privacy, security, and ethical considerations surrounding AI adoption in the public sector, emphasising rigorous security protocols and readiness for large-scale deployment.
Why does it matter?
As generative AI continues to evolve, AWS’s strategic focus on public sector adoption underscores its belief in AI’s transformative potential, aiming to lead the charge in integrating advanced technologies into governmental and non-governmental organisations worldwide.
Chinese AI companies are swiftly responding to reports that OpenAI intends to restrict access to its technology in certain regions, including China. OpenAI, the creator of ChatGPT, is reportedly planning to block access to its API for entities in China and other countries. While ChatGPT is not directly available in mainland China, many Chinese startups have used OpenAI’s API platform to develop their applications. Users in China have received emails warning about restrictions, with measures set to take effect from 9 July.
In light of these developments, Chinese tech giants like Baidu and Alibaba Cloud are stepping in to attract users affected by OpenAI’s restrictions. Baidu announced an ‘inclusive Program,’ offering free migration to its Ernie platform for new users and additional Ernie 3.5 flagship model tokens to match their OpenAI usage. Similarly, Alibaba Cloud provides free tokens and migration services for OpenAI API users through its AI platform, offering competitive pricing compared to GPT-4.
Zhipu AI, another prominent player in China’s AI sector, has also announced a ‘Special Migration Program’ for OpenAI API users. The company emphasises its GLM model as a benchmark against OpenAI’s ecosystem, highlighting its self-developed technology for security and controllability. Over the past year, numerous Chinese companies have launched chatbots powered by their proprietary AI models, indicating a growing trend towards domestic AI development and innovation.
AI startup EvolutionaryScale has secured $142 million in seed funding, led by investors including Nat Friedman, Daniel Gross, and Lux Capital. Both Amazon Web Services (AWS) and NVIDIA’s venture capital arm participated in this substantial funding round. Lux Capital’s co-founder Josh Wolfe likened EvolutionaryScale’s achievements to a ‘ChatGPT moment for biology,’ highlighting their development of a groundbreaking large language model capable of designing new proteins and biological systems.
EvolutionaryScale aims to deploy its AI across diverse applications, from accelerating drug discovery processes to engineering microbes that can degrade plastic pollution. The company’s chief scientist, Alex Rives, emphasised the growing significance of AI in creating innovative biological solutions. That aligns with broader industry trends where AI is increasingly pivotal in advancing biotech and pharmaceutical research.
However, concerns have been raised regarding the potential misuse of generative AI in bioweapons development. Despite these ethical considerations, EvolutionaryScale plans to use its newly secured funding to train its AI models further and expand its team for collaborations within the biotech sector. They have also released the ESM3 models, with the smaller variant open-sourced for non-commercial research, while AWS and NVIDIA will offer the larger ESM3 commercially.
Why does it matter?
One notable achievement highlighted by EvolutionaryScale involves engineering a novel fluorescent protein using their ESM3 model. That protein represents a significant departure from naturally occurring variants, a process typically requiring nature millions of years to evolve. The company’s advancements underscore the transformative potential of AI in pushing the boundaries of biological innovation.
