Jim Cramer makes the case for why Apple and investors should stick with CEO Tim Cook
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
8 minutes ago
- Yahoo
Amylyx Pharmaceuticals Shares Promising Avexitide Data for Post-Bariatric Hypoglycemia at ENDO 2025, Phase 3 Enrollment Nears Completion
Amylyx Pharmaceuticals Inc. (NASDAQ:AMLX) is one of the best low priced pharma stocks to buy now. On July 13, Amylyx Pharmaceuticals announced new exploratory analyses from its Phase 2 PREVENT and Phase 2b clinical trials of avexitide for post-bariatric hypoglycemia/PBH at the Endocrine Society's annual meeting (ENDO 2025). Avexitide is an investigational, first-in-class glucagon-like peptide-1 (GLP-1) receptor antagonist and has received FDA Breakthrough Therapy designation for PBH. PBH is a complication that can arise after bariatric surgery, such as Roux-en-Y gastric bypass. A medical scientist in a lab coat gazing at a microscopic view of a drug in development. There are currently no FDA-approved treatments for PBH. Avexitide works by binding to the GLP-1 receptor on pancreatic islet beta cells, blocking the effect of excessive GLP-1 and thus mitigating hypoglycemia by decreasing insulin secretion and stabilizing glucose levels. Avexitide has generally been well-tolerated with a favorable safety profile across all trials. Amylyx expects to complete recruitment for the LUCIDITY trial this year, with topline data anticipated in H1 2026. Amylyx Pharmaceuticals Inc. (NASDAQ:AMLX) is a clinical-stage pharmaceutical company that discovers and develops treatment options for neurodegenerative diseases and endocrine conditions in the US. While we acknowledge the potential of AMLX as an investment, we believe certain AI stocks offer greater upside potential and carry less downside risk. If you're looking for an extremely undervalued AI stock that also stands to benefit significantly from Trump-era tariffs and the onshoring trend, see our free report on the . READ NEXT: and . Disclosure: None. This article is originally published at Insider Monkey. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
CNN
9 minutes ago
- CNN
Apple just spent $500 million to source a material that's critical for iPhones from the US
Apple is investing $500 million in a deal with US rare earths company MP Materials as the iPhone maker faces pressure from President Donald Trump to produce its popular smartphones domestically. As part of the partnership announced on Tuesday, Apple committed to buying rare earth magnets directly from MP Materials to help bolster its US supply chain. Apple will also collaborate with the company on a new recycling line in California, which will repurpose recycled rare earth materials to use in Apple products. The move is part of a $500 billion investment Apple announced earlier this year to expand its US operations as the Trump administration pushes to onshore technology manufacturing and reduce reliance on China. Rare earths, which are critical for everything from smartphones to TVs and military jets, have been a key bargaining chip in trade talks between Washington and Beijing. That's because China controls nearly all rare earths processing. 'American innovation drives everything we do at Apple, and we're proud to deepen our investment in the US economy,' Apple CEO Tim Cook said in a press release. 'Rare earth materials are essential for making advanced technology, and this partnership will help strengthen the supply of these vital materials here in the United States.' MP Materials' facility in Fort Worth, Texas, will create new magnet manufacturing lines specifically for Apple products. Shipments are expected to begin in 2027 and will eventually support 'hundreds of millions of Apple devices,' according to MP Materials. The materials will be delivered throughout the United States and around the world. Apple says the expansion will create dozens of new jobs. Both companies will also provide training to develop a US workforce for magnet manufacturing. China has a virtual monopoly on rare earth elements, which are critical components for everyday products from smartphones to wind turbines to LED lights and flat-screen TVs. They're also crucial for batteries in electric vehicles as well as MRI scanners and cancer treatments. The name rare earths is also a bit of a misnomer. The materials are found throughout the Earth's crust but are difficult and costly to extract and process. China has the only equipment needed to process some of the various elements and currently controls 92% of the global output in the processing stage. While the MP Materials deal could help Apple curry favor with Trump amid tariff threats, it also aligns with Apple's efforts to incorporate more recycled materials into its products – a plan already in place long before Trump took office. The iPhone 16e, which launched earlier this year, includes 30 percent recycled content, for example. Apple says it uses recycled rare earths in its major products, including in magnets found in the latest iPhones, iPads, Apple Watches, MacBook and Mac models. The Trump administration has been pushing for Apple and other tech giants to produce their products in the United States rather than rely on assembly facilities and supply chain operations largely located in China, India and Vietnam. 'I have long ago informed Tim Cook of Apple that I expect their iPhone's that will be sold in the United States of America will be manufactured and built in the United States, not India, or anyplace else,' Trump posted on Truth Social in May. 'If that is not the case, a Tariff of at least 25% must be paid by Apple to the U.S.' Apple hasn't discussed plans to move iPhone manufacturing to the US, and doing so seems unlikely. That's because it would require the tech giant to upend how it builds its most lucrative product. Critically, Apple and MP Manufacturing's collaboration involves developing the talent pool needed for magnet manufacturing. That's part of the reason why it's so challenging to move iPhone production to the United States – America lacks the highly specialized labor required to do so, experts have said. 'The expertise to make each of the components is something that has to be worked on for a long period of time,' David Marcotte, senior vice president at international market research company Kantar, previously told CNN. Cook has also spoken about the labor gap in the past, describing the workforce in China as being a combination of 'craftsman' skills, 'sophisticated robotics' and 'the computer science world' when speaking at a Fortune Magazine event in 2017. But the commitment to invest in US-sourced rare earths is likely to please Trump. The president has touted Apple's previous investment announcement as a victory in his efforts to boost American manufacturing. Apple is just one of many tech giants that have expanded their American footprint over the past several months. Texas Instruments committed $60 billion to make semiconductors in the United States in June, and Taiwanese chipmaking giant TSMC invested $100 billion in US manufacturing in March. Leading AI chipmaker Nvidia also said it would build its supercomputers in the United States in April. – CNN's Chris Isidore contributed to this report
Newsweek
13 minutes ago
- Newsweek
AI Hiring Favors Women Over Equally Qualified Men, Study Finds
Based on facts, either observed and verified firsthand by the reporter, or reported and verified from knowledgeable sources. Newsweek AI is in beta. Translations may contain inaccuracies—please refer to the original content. As artificial intelligence takes on a bigger role in corporate hiring — with many companies touting its impartiality — one researcher's findings suggest the technology may be more biased than humans, and is alread favoring women over equally qualified men. David Rozado, an associate professor at the New Zealand Institute of Skills and Technology and a well-known AI researcher, tested 22 large language models (LLMs)—including popular, consumer-facing apps like ChatGPT, Gemini, and Grok—using pairs of identical résumés that differed only by gendered names. His findings revealed that every single LLM was more likely to select the female-named candidate over the equally qualified male candidate. "This pattern may reflect complex interactions between model pre-training corpora, annotation processes during preference tuning, or even system-level guardrails for production deployments," Rozado told Newsweek. "But the exact source of the behavior is currently unclear." A Problem With Men? Rozado's findings reveal not just that AI models tend to favor women for jobs over men, but also how nuanced and pervasive those biases can be. Across more than 30,000 simulated hiring decisions, female-named candidates were chosen 56.9 percent of the time — a statistically significant deviation from gender neutrality, which would have resulted in a 50–50 split. When an explicit gender field was added to a CV — a practice common in countries like Germany and Japan — the preference for women became even stronger. Rozado warned that although the disparities were relatively modest, they could accumulate over time and unfairly disadvantage male candidates. "These tendencies persisted regardless of model size or the amount of compute leveraged," Rozado noted. "This strongly suggests that model bias in the context of hiring decisions is not determined by the size of the model or the amount of 'reasoning' employed. The problem is systemic." The models also exhibited other quirks. Many showed a slight preference for candidates who included preferred pronouns. Adding terms such as "she/her" or "he/him" to a CV slightly increased a candidate's chances of being selected. "My experimental design ensured that candidate qualifications were distributed equally across genders, so ideally, there would be no systematic difference in selection rates. However, the results indicate that LLMs may sometimes make hiring decisions based on factors unrelated to candidate qualifications, such as gender or the position of the candidates in the prompt," he said. Rozado, who is also a regular collaborator with the Manhattan Institute, a conservative think tank, emphasized that the biggest takeaway is that LLMs, like human decision-makers, can sometimes rely on irrelevant features when the task is overdetermined and/or underdetermined. "Over many decisions, even small disparities can accumulate and impact the overall fairness of a process," he said. However, Rozado also acknowledged a key limitation of his study: it used synthetic CVs and job descriptions rather than real-world applications, which may not fully capture the complexity and nuance of authentic résumés. Additionally, because all CVs were closely matched in qualifications to isolate gender effects, the findings may not reflect how AI behaves when candidates' skills vary more widely. "It is important to interpret these results carefully. The intention is not to overstate the magnitude of harm, but rather to highlight the need for careful evaluation and mitigation of any bias in automated decision tools," Rozado added. AI Is Already Reshaping the Hiring Process Even as researchers debate the biases in AI systems, many employers have already embraced the technology to streamline hiring. A New York Times report this month described how AI-powered interviewer bots now speak directly with candidates, asking questions and even simulating human pauses and filler words. Jennifer Dunn, a marketing professional in San Antonio, said her AI interview with a chatbot named Alex "felt hollow" and she ended it early. "It isn't something that feels real to me," she told the Times. Another applicant, Emily Robertson-Yeingst, wondered if her AI interview was just being used to train the underlying LLM: "It starts to make you wonder, was I just some sort of experiment?" Job seekers attends the South Florida Job Fair held at the Amerant Bank Arena on June 26, 2024 in Sunrise, Florida. More than 50 companies set up booths to recruit people from entry-level to... Job seekers attends the South Florida Job Fair held at the Amerant Bank Arena on June 26, 2024 in Sunrise, Florida. More than 50 companies set up booths to recruit people from entry-level to management. Open jobs include police officers, food service, security, sales reps, technicians, customer service, IT, teacher assistants, insurance agents, and account executives. More Photo byStill, some organizations defend the use of AI recruiters as both efficient and scalable, especially in a world where the ease of online job-searching means open positions often field hundreds if not thousands of applicants. Propel Impact told the Times their AI interviews enabled them to screen 500 applicants this year — more than triple what they managed previously. Rozado, however, warned that the very features companies find appealing — speed and efficiency — can mask underlying vulnerabilities. "Over many decisions, even small disparities can accumulate and impact the overall fairness of a process," he said. "Similarly, the finding that being listed first in the prompt increases the likelihood of selection underscores the importance of not trusting AI blindly." More Research Needed Not all research points to the same gender dynamic Rozado identified. A Brookings Institution study this year found that, in some tests, men were actually favored over women in 51.9 percent of cases, while racial bias strongly favored white-associated names over Black-associated names. Brookings' analysis stressed that intersectional identities, such as being both Black and male, often led to the greatest disadvantages. Rozado and the Brookings team agree, however, that AI hiring systems are not ready to operate autonomously in high-stakes situations. Both recommend robust audits, transparency, and clear regulatory standards to minimize unintended discrimination. "Given current evidence of bias and unpredictability, I believe LLMs should not be used in high-stakes contexts like hiring, unless their outputs have been rigorously evaluated for fairness and reliability," Rozado said. "It is essential that organizations validate and audit AI tools carefully, particularly for applications with significant real-world impact."
