Latest news with #RAFT
Geeky Gadgets
11-06-2025
- Business
- Geeky Gadgets
How RAFT is Making AI Smarter, Faster, and More Accurate Than Ever
What if artificial intelligence could think beyond its training, pulling in fresh insights from the vast expanse of human knowledge? Imagine an AI model that doesn't just rely on static datasets but actively retrieves the latest medical research, legal precedents, or financial trends to inform its decisions. This is no longer a futuristic dream—it's the promise of Retrieval-Augmented Fine-Tuning (RAFT). By blending the precision of fine-tuning with the adaptability of retrieval systems, RAFT redefines how AI learns and evolves, making it a fantastic option for industries where accuracy and context are non-negotiable. But with such fantastic potential comes a critical question: how does this hybrid approach actually work, and what makes it so effective? In this exploration of RAFT, the IBM Technology team uncover the mechanics behind this innovative technique and its ability to bridge the gap between static training data and the ever-changing real world. You'll discover how RAFT enables AI to handle complex, domain-specific challenges with unprecedented accuracy, from diagnosing rare medical conditions to navigating intricate legal frameworks. Along the way, we'll delve into its core components, practical applications, and the challenges that lie ahead. Whether you're curious about the future of machine learning or seeking innovative solutions for your field, RAFT offers a glimpse into a smarter, more adaptable AI. After all, what could be more powerful than an AI that learns not just from the past, but also from the present? Overview of RAFT The Mechanism Behind RAFT RAFT functions as a dynamic and adaptive training process, improving upon traditional fine-tuning by incorporating retrieval systems. These systems enable AI models to access and retrieve relevant external knowledge during training, rather than relying solely on static datasets. This dynamic retrieval ensures that the model remains aligned with the most current and accurate information available. For example, consider training an AI model to address complex medical queries. With RAFT, the model can retrieve the latest medical research, guidelines, or case studies during its training phase. This ensures that the model's responses are not only accurate but also reflective of the most up-to-date knowledge in the field. By integrating external data sources, RAFT bridges the gap between static training data and the ever-evolving nature of real-world information. Core Components Driving RAFT The effectiveness of RAFT lies in its integration of several critical components, each contributing to its ability to generate precise and context-aware outputs: Retrieval Systems: These systems are designed to identify and extract relevant information from extensive datasets or databases, making sure the model has access to the most pertinent knowledge. These systems are designed to identify and extract relevant information from extensive datasets or databases, making sure the model has access to the most pertinent knowledge. Fine-Tuning Techniques: Fine-tuning adjusts the model's internal parameters based on the retrieved knowledge, enhancing its ability to produce accurate and contextually appropriate outputs. Fine-tuning adjusts the model's internal parameters based on the retrieved knowledge, enhancing its ability to produce accurate and contextually appropriate outputs. External Knowledge Integration: By incorporating external data sources, RAFT ensures that models are not limited to static training datasets, allowing them to adapt to dynamic, real-world information. By incorporating external data sources, RAFT ensures that models are not limited to static training datasets, allowing them to adapt to dynamic, real-world information. Contextual Reasoning: RAFT improves the model's capacity to understand and process complex relationships within data, resulting in nuanced and precise outputs. RAFT improves the model's capacity to understand and process complex relationships within data, resulting in nuanced and precise outputs. Domain-Specific Knowledge: This approach is particularly effective in specialized fields where accurate and context-aware information is essential for success. What is Retrieval-Augmented Fine-Tuning (RAFT)? Watch this video on YouTube. Here are additional guides from our expansive article library that you may find useful on AI learning. Practical Applications of RAFT The versatility of RAFT makes it applicable across a wide range of industries and use cases. In natural language processing (NLP), RAFT enhances tasks such as question answering, text summarization, and conversational AI. For instance, customer support chatbots equipped with RAFT can retrieve real-time product information, allowing them to provide more precise and contextually relevant responses to user queries. In the realm of scientific research, RAFT can analyze vast datasets by retrieving relevant studies or data, helping researchers draw accurate and insightful conclusions. Similarly, in legal and regulatory fields, RAFT ensures that AI models remain updated with the latest laws, regulations, and guidelines, thereby improving compliance and decision-making accuracy. These applications highlight RAFT's ability to adapt to the specific needs of various domains, making it a valuable tool for tackling complex challenges. Advantages and Potential of RAFT RAFT offers a range of benefits that extend beyond traditional fine-tuning approaches. By integrating external knowledge retrieval, RAFT enables AI models to: Handle Complex Queries: RAFT equips models to process intricate and multi-faceted queries that require deep contextual understanding. RAFT equips models to process intricate and multi-faceted queries that require deep contextual understanding. Adapt to Evolving Information: By incorporating up-to-date knowledge during training, RAFT ensures that models remain relevant in dynamic environments. By incorporating up-to-date knowledge during training, RAFT ensures that models remain relevant in dynamic environments. Excel in Specialized Fields: RAFT is particularly effective in domains such as medicine, law, and finance, where static training data often falls short of capturing the complexity of real-world scenarios. RAFT is particularly effective in domains such as medicine, law, and finance, where static training data often falls short of capturing the complexity of real-world scenarios. Produce Contextually Relevant Outputs: By retrieving and integrating external knowledge, RAFT ensures that the outputs generated are tailored to the specific context of a given query or task. Challenges and Future Prospects While RAFT offers significant advantages, it also presents certain challenges. The retrieval process can be computationally intensive, requiring robust infrastructure to manage and process large-scale data efficiently. Additionally, making sure the quality and relevance of the retrieved information is critical to maintaining the accuracy and reliability of the model's outputs. Looking ahead, ongoing research aims to optimize retrieval mechanisms and incorporate more diverse data sources into the RAFT framework. These advancements are expected to enhance the efficiency and adaptability of RAFT, allowing AI models to tackle increasingly complex tasks with greater precision. As the field of machine learning continues to evolve, RAFT's ability to integrate external knowledge and improve contextual reasoning will play a pivotal role in addressing the growing demands of AI applications. Media Credit: IBM Technology Filed Under: AI, Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
BBC News
13-05-2025
- General
- BBC News
Somerset winter coat exchange receives thousands of donations
A scheme in which people donate winter coats to libraries has become a "heart-warming success".A total of 15 libraries in Somerset, including Taunton, Bridgwater and Yeovil, accepted donations over the winter year 2,470 coats for both adults and children were donated - more than double the figure received in Federica Smith-Roberts, lead member for communities at Somerset Council, said: "The success of the Winter Coat Exchange is a testament to the power of community." The initiative is designed to support the community by providing access to warm coats for everyone, especially those who may struggle to afford the winter period 2,086 coats were taken by people in need, with left over items donated to local refugee charity Refugee Aid From Taunton (RAFT).RAFT supports displaced people locally and further Smith-Roberts said: "I just find it really heart-warming for people to come forward to donate items that they don't need.""The items are put on a coat stand and people can take them, no questions asked."She added: "By encouraging the reuse of coats, the initiative also helps to reduce waste."
Yahoo
07-05-2025
- Business
- Yahoo
Ludlow mobile home park residents sue owner in 2 cases of housing discrimination
LUDLOW — When Kerwin Ortiz told his landlord that he would be using state assistance to pay for a month of missed rent, the owner refused to accept it. Now, Ortiz is suing Thomas Lennon, alleging that he discriminated against him for using public assistance toward his rental payment, according to the complaint filed April 1. Ortiz lives at West Street Village Mobile Home Community in Ludlow. While he owns his mobile home, he still pays rent on the lot. Over the last few months, Lennon raised the rents by 143%, jumping from $207 to $503, an increase most at the park can't afford. Many of the residents who live there are older, earn little income and/or are disabled. After dealing with some financial troubles near the end of February, he told Lennon in a text exchange that he'd use Way Finders' rental assistance to pay for rent, which is passed through to the agency from the state. 'I'm not accepting wayfinders (sic),' Lennon texted Ortiz, according to an exhibit in the complaint. 'Is there an assistance program you do accept?' Ortiz replied. 'No, it's a ton of paperwork a huge project for ME and I may or may not get the rent in 10 weeks,' Lennon texted back. The complaint alleges Lennon's actions in refusing to accept any form of state rental assistance from Ortiz were 'intentional and willful' with 'reckless disregard for the civil rights of the plaintiff.' Refusing to accept rental aid is a violation of fair housing laws, the lawsuit alleges. Ortiz is being represented by Joel Feldman, a Springfield housing attorney for Heisler, Feldman and Ordorica PC, and Destin Germany of the Central West Justice Center in Springfield. In a statement, Ortiz said tenants like him in a mobile home park are 'vulnerable to aggressive rent hikes.' While Massachusetts offers rental aid such as from the Residential Assistance for Families in Transition program, 'this option had been refused by our landlord,' he said in the statement. 'Actions like (the landlord's) allows individuals to unilaterally price out people they deem 'undesirables,' which would keep families like ours from ever being parts of communities like this,' he said. Feldman is expecting Lennon's reply in court within the next couple of days, he told The Republican. Other claims against Lennon Ortiz is not alone in his housing discrimination claims. In a lawsuit filed Monday, Lisa Pacheco, another West Street Village resident, alleged that when she told Lennon she could not make a monthly rent payment because of a serious health condition, Lennon again said he would not accept rental assistance from Way Finders. Lennon reportedly told Pacheco that it would be 'too much paperwork,' according to her complaint. When Pacheco told Lennon that she already had been approved for RAFT funding for her utility payments, and that it wouldn't be too much paperwork for Lennon, he allegedly said he was not 'willing to accept RAFT payments for rent, and that he would not go down that route.' At least two other residents were denied use of rental assistance, according to Pacheco's complaint. Both lawsuits say that, as a housing provider, Lennon and landlords like him must 'abide by state fair housing laws in their acceptance of state rental assistance programs.' Lennon's attorney, Robert Kraus of Kraus and Hummel in Plymouth, could not be reached for comment. Fighting back against rent increases Feldman also is representing three West Street Village mobile home park residents who filed an appeal last April on the Ludlow Mobile Home Rent Control Board's decision in July 2023 to increase the rent of the lots by almost $300. Judge Jonathan Kane, a state Housing Court judge, ordered in late March that the board's decision to increase the rent was not allowed. His reasoning was that two of the board members, who were not present for the vote, did not certify under oath that they reviewed the record of the proceedings, which violated a state law. Lennon, as owner, and Kraus, his attorney, are intervenors, meaning they are a third party in that case. Kraus filed a notice of appeal at the end of March, but he has not filed an official appeal in court. The case is ongoing, Feldman explained in a phone call Tuesday. 'We are waiting for the judge to decide whether the decision should be returned to the rental control board to decide on the rent after reviewing the record,' said Feldman. 'It would be premature for them to file an appeal at this point.' more news from Western Massachusetts Read the original article on MassLive.
Yahoo
03-04-2025
- Business
- Yahoo
Mass. Gov. Healey seeks $756 million for ‘time-sensitive deficiencies'
On the eve of a legislative hearing on her surtax surplus plan, Gov. Maura Healey submitted another spending bill for the Legislature's review, filing a $756 million supplemental budget she said would address 'time-sensitive deficiencies' in state government accounts. The proposal Healey filed Wednesday afternoon (HD 4540) includes $134.5 million for supplemental payments to safety-net hospitals, $60 million for direct care for older adults, $240 million for state employee health care costs through the Group Insurance Commission, and more. It would carry a net state cost of $544 million after federal reimbursements, she said. Healey's office pitched the $190 million the bill includes for a child care financial assistance program as a way to 'support Massachusetts residents at a time of rising costs.' Another $43 million would go toward the Residential Assistance for Families in Transition (RAFT) program that offers aid to families facing potential eviction, which has faced increasing demand during a period of housing strain. The legislation additionally includes $15 million for grants and marketing related to the American Revolution 250th anniversary celebration, and $15.5 million for more secure electronic benefits transfer cards that Healey said would 'help combat food benefit theft.' 'This budget bill proposes targeted investments that improve quality of life in Massachusetts, such as ensuring access to health care, supporting families with child care costs, and making sure veterans get their benefits,' Healey said in a statement alongside the bill. 'We've also heard clearly from local officials and medical professionals across the state, especially in communities impacted by Steward Health Care's closures, that they need more support. That's why we're proposing significant funding for EMS providers that have faced extraordinary costs. Our administration remains committed to maintaining a responsible state budget that tangibly benefits the people of Massachusetts.' Other sections of the 25-page bill would ratify collective bargaining agreements with public employees, raise procurement thresholds under public construction laws, and allow Massachusetts Emergency Management Agency vehicles to use red and blue lights when responding to emergencies. The Legislature's Joint Committee on Ways and Means is partway through a series of hearings about Healey's $62 billion fiscal 2026 state budget, and the panel will meet Thursday to consider Healey's separate $1.3 billion proposal (H 55) to spend surplus surtax revenue. Download the FREE Boston 25 News app for breaking news alerts. Follow Boston 25 News on Facebook and Twitter. | Watch Boston 25 News NOW
Yahoo
04-03-2025
- Business
- Yahoo
Ex-state employee gets prison time for defrauding Mass. housing agency after being fired from job
A former state employee will serve time in federal prison for defrauding a Massachusetts housing agency after being fired from her job, and defrauding the U.S. Small Business Administration in connection with the pandemic Paycheck Protection Program. Alihea Jones, 51, of Brandon, Fla., was sentenced in federal court to 10 months in prison, to be followed by three years of supervised release, U.S. Attorney Leah Foley said in a statement on Monday. Jones was also ordered to pay $222,074 in restitution and to forfeit $222,074. U.S. District Court Judge Patti B. Saris handed down Jones' sentence. In September 2024, Jones pleaded guilty to five counts of wire fraud. In 2022, Jones worked remotely for the Massachusetts Department of Housing and Community Development for six months, Foley said. She worked with the agency's Residential Aid to Families in Transition program, which provides funds to assist low-income Massachusetts residents facing eviction and other housing emergencies. Prosecutors said after Jones was fired from the agency, she was still logged into the RAFT database and accessed the files of four RAFT program participants. She authorized electronic payments to their landlords in the amounts of $7,500, $8,800, $6,925 and $10,000. Jones changed the routing and bank account numbers from the landlords' accounts to four unauthorized accounts in Georgia: an account in the name of Jones's business, Beauty Concepts by Alihea LLC; Jones's personal account; and the accounts of two of her friends. Jones did this 'all without knowledge or permission' from the state agency, prosecutors said. After the transfers went through, her two friends each paid Jones a $2,000 kickback, prosecutors said. Earlier, in 2021, Jones also fraudulently obtained a $187,000 PPP loan from a Massachusetts lender, which the SBA later forgave, prosecutors said. Jones spent most of the money on personal expenses, including clothing and restaurants. Under the PPP, authorized lenders issued SBA-guaranteed loans to small businesses during the COVID pandemic to help keep workers employed. If a business spent the money on payroll and other permissible business expenses, the SBA forgave the loan. Jones submitted a PPP loan application to a Massachusetts lender falsely stating that Beauty Concepts had 17 employees and an average monthly payroll expense of $74,800, prosecutors said. In fact, Beauty Concepts did not employ anyone. Unaware that Jones's information was false, the SBA agreed to guarantee a $187,000 loan to Beauty Concepts, prosecutors said. The lender transmitted the loan proceeds to the Beauty Concepts account in Georgia. Jones later applied to have her loan forgiven. 'Again, she included false employee count and payroll information,' the U.S. Attorney said in her statement. 'Unaware that Jones's representations were false, the SBA forgave the loan principal and accrued interest.' In total, Jones caused a loss of $222,074, with $33,225 payable to the Department of Housing and Community Development and $188,849 payable to the SBA, Foley said. This is a developing story. Check back for updates as more information becomes available. Download the FREE Boston 25 News app for breaking news alerts. Follow Boston 25 News on Facebook and Twitter. | Watch Boston 25 News NOW
