"Open source software quietly affects nearly every issue in AI policy," wrote Alex Engler in a Brookings Institution briefing, yet this is barely discussed by government policymakers. This is a mistake, and it's one that crosses the political aisle. The Trump administration barely mentioned open source in its AI policies, while the Obama administration touted open source as driving AI innovation but stopped there. In Europe things are no better, with new regulations about AI skipping the topic of open source entirely. Given how prevalent open source has become in the artificial intelligence software that companies and governments use, policymakers would do well to pay attention, noted Engler.

The world is transforming into a digital environment at an unprecedented rate, and the transformation will only accelerate. Everything – business, entertainment, trends, new goods, etc. is moving at breakneck speed due to digitalization. Because the service provider has the resources to provide, the customer receives what they want right away. While the advantages and benefits of the digital age are numerous, it also has several drawbacks. One of the most severe and damaging risks it poses is that our personal information is now more vulnerable than ever.

Sooner or later, the concept of digitization will completely take over all repetitive tasks. Today, with the help of big data, advanced technologies like automation, artificial intelligence, IoT, and machine learning are leveraging unimaginable amounts and types of information to work from. It is streamlining tedious, repetitive, and difficult tasks, which tend to slow down production and also increases the cost of operation. Owing to the evolution of technology, artificial intelligence startups are mushrooming like never before. The companies are driving the world into a new phase of digitization with a mixture of disruptive statistical methods, computational intelligence, soft computing, and traditional symbolic AI. Artificial intelligence is the combination of two amazing concepts namely science and engineering. With the infusion of disruptive trends and human intelligence, intelligent machines and intelligent computing programs are emerging. Slowly, the flare of innovations moved away from IT and entered into diverse industries including healthcare, education, finance, marketing, business, telecommunication, etc. Organizations realized that by digitizing repetitive tasks, an enterprise can cut the cost of paperwork and labor which further eliminates human error, thus boosting efficiency. Automating processes involve employing artificial intelligence solutions that can support digitization and deliver data-driven insights. Artificial intelligence startups emerge as a ready-made solution provider that supports every company's individual needs. AI startups in 2021 use big data to sophisticated AI models and leverage new solutions that could better serve customers. Analytics Insight has listed the top 100 artificial intelligence startups that are driving the next-generation development in technology. It democratizes the way investments are done by bringing sophisticated elite trading technology to laymen. Accrad is a health tech company that assists radiologists to reduce their workload with the precision of artificial intelligence. Radiologists work under different circumstances and deadlines and might find diagnosis through x-rays a bit difficult. Therefore, Accrad has come up with a futuristic solution to help with accurate and fast image diagnosis. The company has made x-ray processing more convincing and simpler. Its signature product CheXRad, a deep learning algorithm that identifies locations in the chest radiograph has the capability to predict 15 different diseases including Covid-19. Affable.ai is a data-driven influencer marketing platform where customers can find relevant and authentic influencers and manage marketing operations. By using cutting-edge computer vision algorithms on social media posts, the company delivers actionable insights about micro-influencers and their audience. Similar to how Google has sophisticated its search and promote relative ads to users, Affable.ai has also built one-click marketing at a shorter scale.

FINGER LAKES – A radical collaboration between a Cornell biologist and an engineer is supercharging efforts to protect grape crops. The technology they've developed, using robotics and artificial Intelligence (AI) to identify grape plants infected with a devastating fungus, will soon be available to researchers nationwide working on a wide array of plant and animal research. The biologist, Lance Cadle-Davidson, Ph.D. '03, an adjunct professor in the School of Integrative Plant Science (SIPS), is working to develop grape varieties that are more resistant to powdery mildew, but his lab's research was bottlenecked by the need to manually assess thousands of grape leaf samples for evidence of infection. Powdery mildew, a fungus that attacks many plants including wine and table grapes, leaves sickly white spores across leaves and fruit and costs grape growers worldwide billions of dollars annually in lost fruit and fungicide costs. Cadle-Davidson is also a research plant pathologist with the U.S. Department of Agriculture's Agricultural Research Service (USDA-ARS).

The Transform Technology Summits start October 13th with Low-Code/No Code: Enabling Enterprise Agility. Governments face a range of policy challenges around AI technologies, many of which are exacerbated by the fact that they lack sufficiently detailed information. A whitepaper published this week by AI ethicist Jess Whittlestone and former OpenAI policy director Jack Clark outlines a potential solution that involves investing in governments' capacity to monitor the capabilities of AI systems. As the paper points out, AI as an industry routinely creates a range of data and measures, and if the data was synthesized, the insights could improve governments' ability to understand the technologies while helping to create tools to intervene. "Governments should play a central role in establishing measurement and monitoring initiatives themselves while subcontracting out other aspects to third parties, such as through grantmaking, or partnering with research institutions," Whittlestone and Clark wrote.

The U.S. Army Research Lab made breakthroughs this summer on two neural networks projects that could assist commanders' decision-making on the battlefield and provide soldiers' health information through fibers in their uniform. The advancements come as the U.S. military is preparing for data-driven battle, in which gobs of data are transmitted across the battlespace, processed and used in a commander's decision-making. Neural networks are a combination of algorithms that work together to recognize patterns in data through a process similar to that of the human brain. The first project is working to provide a tool to battle commanders that quantifies uncertainty in data analysis using neural networks. Researchers associated with the Army Research Lab created a new framework for neural network processing that would use artificial intelligence to provide confidence ratings.

Artificial Intelligence and its inherent bias seems to be an ongoing contributing factor in slowing minorities home loan approvals. An investigation by The Markup found lenders were more likely to deny home loans to people of color than to white people with similar financial characteristics. Specifically, 80% of Black applicants are more likely to be rejected, along with 40% of Latino applicants, and 70% of Native American applicants are likely to be denied. How detrimental is the secret bias hidden in mortgage algorithms? It's important to note that 45% of the country's largest mortgage lenders now offer online or app-based loan origination, as FinTech looks to play a major role in reducing bias in the home lending market, CultureBanx reported.

Tiny flying drones, dubbed'slaughterbots', with facial recognition software and weapons capable of mass murder could be the future of warfare. A group of professors have warned the technology is already available to create flying mini killing machines. The Future of Life Institute (FLI), an artificial intelligence watchdog backed by the likes of physicist Stephen Hawking, has produced this chilling video demonstrating how these'slaughterbots' could kill thousands of people. The film is a vision of a dystopian future where tiny drones equipped with explosives, cameras, sensors and face scanners can programmed to carry out deathly instructions by either governments or terrorists. The UN Convention on Conventional Weapons summit in Geneva screened the film and also was heard stark warnings about the growing danger of drone warfare.

The location of the drone strike is in a heavily built-up part of Kabul called Khaje Bughra, near the airport. Relatives and neighbours in the area have disputed the justification for the strike, telling journalists that US intelligence was wrong, and that there was no Islamic State presence in the area.

Watch'The Lost Calls of 9/11' Sunday, Sept. 5 at 10 p.m. ET on Fox News. President Biden on Friday signed an executive order calling for the review of classified information related to the terrorist attacks on Sept. 11, 2001, and the ultimate declassification of some documents. The president's move was lauded by families of victims who died on that fateful day nearly 20 years ago, and was seen as a supportive gesture toward many who have long sought the records in hopes of implicating the Saudi government. The order, coming little more than a week before the 20th anniversary of the attacks, is a significant moment in a yearslong tussle between the government and the families over what classified information about the run-up to the attacks could be made public. That conflict was on display last month when some 1,800 relatives, survivors and first responders came out against Biden's participation in 9/11 memorial events if the documents remained declassified.