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IBM aspires to make a lasting, positive impact on the world by protecting the environment, advocating for inclusion, and fostering trust and transparency in both technology and business. Today’s IBM is more closely aligned with the needs of our clients. Our engagement model is simpler and more effective. And we have expanded our ecosystem by strengthening existing relationships and forging new, productive partnerships.
Today’s IBM is not simply a technology company. We are a problem-solving company and a convener of capability that brings together our colleagues, our clients, and our partners with a simple, open invitation: Let’s create. we have sharpened our focus on IBM’s unique ability to integrate technology and business expertise for our clients and our partners. Our portfolio is built around hybrid cloud and artificial intelligence (AI), the two most transformational technologies of our time.
Our go-to-market approach brings together the necessary software, consulting, and infrastructure our clients require, from across our expanding ecosystem of partners. They recognize technology as a source of competitive advantage, capable of addressing these immediate issues and future-proofing their businesses by increasing productivity, reducing costs, driving innovation, and fueling growth.
This is today’s IBM.
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Change Company | Change Company | Change Company | ||
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Overall Rating | 4.0/5 based on 22.1k reviews | 3.6/5 based on 39.5k reviews | 3.7/5 based on 90.1k reviews | 3.7/5 based on 53.2k reviews |
Highly Rated for | Work-life balance Skill development Job security | Job security | Job security Work-life balance | Job security |
Critically Rated for | Promotions | Salary Promotions Work satisfaction | Promotions Salary Work satisfaction | Promotions Salary |
Primary Work Policy | Hybrid 80% employees reported | Hybrid 86% employees reported | Work from office 81% employees reported | Hybrid 62% employees reported |
Rating by Women Employees | 4.0 Good rated by 6.9k women | 3.7 Good rated by 11.8k women | 3.8 Good rated by 26.1k women | 3.8 Good rated by 15.2k women |
Rating by Men Employees | 4.0 Good rated by 14k men | 3.5 Good rated by 25.1k men | 3.6 Good rated by 58.8k men | 3.7 Good rated by 35.5k men |
Job security | 4.0 Good | 4.1 Good | 4.5 Good | 3.8 Good |
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Trump to meet tech leaders facing import tariffs and stricter export rules
- A group of tech CEOs, including those from HP, Intel, IBM, and Qualcomm, are discussing a meeting with the Trump administration to address import tariffs and stricter export rules.
- The CEOs want to discuss trade policy, US manufacturing, and potential restrictions on the export of advanced technology for AI data centers.
- The White House is promoting policy changes that may disrupt global supply chains and make manufacturing in China more expensive for the computer-hardware industry.
- Trump has called for Congress to revoke the 2022 Chips Act, which provides incentives to companies like Intel and Taiwan Semiconductor Manufacturing Co.
The Moral Limits of AI in Decision-Making
- As AI is increasingly integrated into decision-making processes with moral implications, concerns arise regarding its capabilities in facing moral dilemmas and potential mistakes, prompting a discussion on the level of trust placed in AI for impactful decisions.
- AI lacks the ability to consider values, emotions, and experiences that influence human ethical choices, as it operates on statistical calculations and data patterns, devoid of consciousness or understanding of morality.
- While AI can mimic some moral values without true comprehension, the subjective and situational nature of ethics makes it challenging to program objective morality into machines, leading to potential conflicts with broader ethical principles.
- The example of a hospital AI recommending oncology treatments highlights how AI's data-driven decisions may not align with personalized patient preferences and circumstances, posing ethical dilemmas about responsibility and the implications of AI-driven decisions on individuals.
- Cases like the IBM Watson Health AI and the COMPAS system demonstrate the limitations and risks of AI in crucial decision-making contexts such as medicine and criminal justice, emphasizing the need for human oversight and caution in relying on AI independently.
- AI, despite its utility in analyzing data and detecting patterns, lacks moral judgment, empathy, and an understanding of human context, making it unsuitable for autonomous decision-making in contexts requiring sensitivity and ethical discernment.
- The failures of AI systems like IBM Watson Health and COMPAS underscore the importance of supervised and limited AI use in complementing human decision-making processes rather than replacing human judgment, especially in areas where lives are at stake.
- AI's potential biases, as seen in systems like COMPAS reflecting historical disparities, raise concerns about the objectivity and accuracy of AI-driven decisions, particularly in judicial systems where biases could lead to unjust outcomes.
- The overarching question pertains not only to AI's capability but also its appropriateness in making moral decisions; until AI can understand and navigate the nuanced ethical complexities of human contexts, human oversight and final judgment remain crucial.
- In essence, while AI can be a valuable tool in various fields, its limitations in grasping empathy, moral nuances, and contextual understanding necessitate a cautious approach in utilizing AI for decision-making roles that involve moral and ethical considerations.
- The crux lies in striking a balance between leveraging AI's analytical capabilities and preserving human moral judgment and empathy in critical decision-making processes to uphold ethical standards and prevent potential harm or bias.

Qld Transport plans mainframe shift as CITEC ends support
- Queensland’s Department of Transport and Main Roads plans to transfer its TRAILS system, hosted on an IBM z16 mainframe managed by state-run IT provider CITEC, to the cloud, due to the discontinued IT support services by CITEC.
- The move is driven by the department's aim to reduce its dependency on CITEC and to modernize the 30-year-old transport registration and integrated licensing system.
- The TRAILS system, described as a highly complex legacy system, is currently hosted in data centers operated by Polaris and iSeek but can be migrated to cloud services hosted in Sydney or Melbourne.
- By migrating to the cloud, the department aims to ensure continuity of services and create a modernization roadmap for TRAILS and the Registration and Licensing Services ecosystem.
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The Quantum ChatGPT Moment is Arriving (And It's Bigger Than You Think)
- The article discusses the potential of quantum computing, highlighting its revolutionary nature and the vast opportunities it offers for research students.
- Rather than incremental advancements, quantum computing represents a paradigm shift that demands pioneers and visionaries.
- Quantum computing leverages qubits, which can exist in superposition and entanglement, enabling exponential speedups and vast computational possibilities.
- The field is transitioning from theoretical physics into tangible hardware and software, attracting significant investments and creating a new industry.
- Research students have a unique playground for exploration in quantum computing, with untapped potentials in quantum-enhanced machine learning, quantum simulation, and quantum optimization.
- The article draws parallels between the potential 'ChatGPT moment' in generative AI and the possible breakthroughs in hybrid quantum-classical computing and Quantum AI synergy.
- Key areas for potential groundbreaking discoveries include quantum-enhanced machine learning, quantum simulation, quantum-inspired classical algorithms, and quantum optimization.
- Research students are encouraged to immerse themselves in quantum computing through hands-on platforms like IBM Quantum Experience, Amazon Braket, Microsoft Azure Quantum, and others.
- The article also recommends resources and courses for aspiring researchers in quantum computing to build a strong foundation and embark on their quantum odyssey.
- By choosing quantum computing, individuals are not just pursuing a career but embarking on an odyssey into the unknown, shaping the future of computation and solving humanity's challenges.

Fermilab’s Anna Grassellino: eyeing the prize of quantum advantage
- The Superconducting Quantum Materials and Systems (SQMS) Center, led by Fermi National Accelerator Laboratory (Chicago, Illinois), aims to develop advanced quantum computers and sensors using technologies from particle accelerators.
- Established under the US National Quantum Initiative, SQMS is funded with $115m to address scientific challenges in quantum computing and sensors with 35 partner institutions.
- The focus is on extending the coherence time of superconducting quantum states for efficient information storage and processing in qubits.
- SQMS has made progress in reducing decoherence in qubits, achieving improved lifetimes and performance stability in quantum processors.
- The collaboration works on technology transfer, quantum processor advancements, and quantum sensors for various applications, including in particle physics and MRI research.
- Research efforts include scaling cryogenic systems for more qubits per refrigerator, optimizing microwave interconnects, and building strong partnerships with industry and academic institutions.
- Collaborations with companies like Rigetti and IBM focus on enhancing quantum processors, developing quantum interconnects, and simulating physics problems using quantum computing.
- Partnerships with suppliers and capacity-building initiatives, like the Quantum Garage laboratory, support SQMS's quantum R&D and technology innovation goals.
- SQMS plans to continue coherence research, advance 3D SRF cavity-based quantum computing, and work on scaling quantum systems for large data centers with millions of qubits.
- The center emphasizes quantum workforce development through recruitment, annual educational events like the US Quantum Information Science School, and discussions on launching a master's degree in quantum engineering.

Building RAG from the Ground Up: A Journey from High Costs to High Impact
- The process of extracting and organizing data from complex SOPs and department heads was proving to be a logistical nightmare.
- The idea of using Retrieval-Augmented Generation (RAG) for this task led to the discovery of IBM's NeuralSeek.
- Despite the steep learning curve, the team successfully fine-tuned the AI model and achieved incredible results.
- To reduce the cost of goods sold (COGS) from 190% to 15%, a decision was made to build an in-house RAG solution.

From Scalpels to Screens: Revolutionizing Medical Insights with Immersive Data Visualization (Part…
- The article discusses how AI, Virtual Reality, and Augmented Reality enhance decision-making, patient care, and education in the medical field through immersive data visualization.
- AI integration with immersive visualization improves healthcare professionals' ability to detect critical patterns and make informed decisions, especially in areas like oncology.
- The collaboration between Cleveland Clinic and IBM showcases how immersive data visualization with AI and quantum computing enhances decision-making and biomedical insights.
- Virtual Reality (VR) is utilized for managing phobias and PTSD, offering controlled exposure therapy to patients in safe environments, such as treating fear of flying and heights.
- Immersive visualization plays a crucial role in patient education by providing clearer insights into conditions and treatments, aiding in making informed choices.
- VR is proving to be an effective tool for pain management in acute and chronic settings by engaging multiple senses to distract from pain perception.
- Despite promising results, more research is needed to explore the full potential of VR in chronic pain management and its integration with other therapeutic modalities.
- Overall, immersive technologies like VR and AR are transforming biomedical insights, procedural mastery, surgical planning, training, and patient care, fostering better outcomes and informed decisions.
- Future articles will delve deeper into the impact of immersive experiences on decision-making and patient care, highlighting advancements in medical education and clinical practice.
- References: Bravemind, Cleveland Clinic and IBM, Visualization of health information, Virtual Reality exposure effect in acrophobia, Virtual reality and pain management, MindMaze, Phobias Suite.
The Ethical Dilemmas of AI in Decision-Making
- AI is increasingly being utilized to make decisions with moral implications, such as resource distribution and job candidate selection, prompting ethical dilemmas and concerns about trust in AI decision-making.
- Human decision-making considers values and emotions, while AI relies on statistical calculations and lacks comprehension of morality, posing challenges in programming objective morality into machines.
- AI may replicate moral values without understanding them, and the subjective nature of ethical values makes it difficult to program universal morality into AI systems.
- AI is optimized for efficiency within set parameters, potentially conflicting with broader ethical principles in decision-making scenarios.
- The example of AI recommending personalized cancer treatments highlights the ethical complexities of AI decisions impacting individuals' lives beyond statistical probabilities.
- Case studies like IBM Watson Health's failure in real-world medical cases and COMPAS system's racial bias highlight the limitations and risks of AI decision-making in critical areas like healthcare and criminal justice.
- AI's reliance on historical data can perpetuate biases and inaccuracies in decision-making processes, leading to questions about its objectivity and reliability.
- While AI can assist in data analysis and pattern detection, its lack of empathy and moral judgment necessitates human oversight in decision-making that involves sensitivity, empathy, and human context.
- Artificial intelligence should be viewed as a complementary tool rather than a replacement for human judgment in critical decision-making processes to prevent potential immorality and harm.
- The discussion around AI's role in making moral decisions raises questions about dehumanizing societal processes and emphasizes the importance of human involvement and oversight in ethical decision-making.
- As AI continues to evolve, considerations about its limitations in understanding ethical complexities and human contexts remain vital, highlighting the ongoing need for human involvement in moral decision-making.

The first 5MB hard drive weighed approximately...
- The first 5MB hard disk unit weighed over a ton (approximately 2,200 pounds) and was used in the IBM 305 RAMAC, the first commercial computer to feature a moving-head hard disk.
- The drive occupied 16 square feet and utilized fifty 24-inch platters, which were read by two independently moving arms with an average access time of 600 milliseconds.
- At the time, 5MB of storage provided the ability to store five million characters of accounting data – the equivalent of 64,000 punch cards or approximately 2.5 million pages of typed text.
- Production of the IBM 305 RAMAC ended in 1961, as it became obsolete following the introduction of IBM's 1405 Disk Storage Unit for the IBM 1401 computer.
How e& and IBM are shaping the future of AI and FinTech innovation
- The telecommunications industry is rapidly evolving towards AI, FinTech, and content services to create new revenue streams and compete with OTT providers.
- AI in telecommunications is driving enhanced customer experiences and operational efficiencies, with e& focusing on telecom operations integrated with advanced technology solutions.
- Harrison Lung of e& discussed the growth in revenue and net profit through AI journey, foreseeing AI's significant impact by 2025.
- AI is reshaping the telecom industry by optimizing networks, personalizing content, improving cybersecurity, and driving operational efficiencies.
- Despite the opportunities AI provides, challenges remain in regulation, governance, and data compliance across different countries.
- Partnerships like e& and IBM are driving AI governance, research, and enterprise solutions to ensure responsible AI implementation and compliance.
- Beyond research, e& and IBM are collaborating on an AI governance framework for transparency, compliance, and ethical AI usage across industries.
- IBM's global presence and technology portfolio offer valuable insights and expertise for e& to leverage in scaling its technology ambitions.
- The partnership aims to develop an end-to-end AI governance platform and framework to manage AI initiatives and processes effectively.
- The collaboration focuses on ensuring compliance, transparency, and governance in AI operations while leveraging IBM's expertise and infrastructure.

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