The Beat: Chicago's quantum scene strikes multiple deals
The Big One
As local lawmakers and industry leaders continue to pursue their vision for making Illinois a global capital for quantum computing, more corporate partners and tech giants want to get involved.
GET TO KNOW YOUR CITY
Find Local Events Near You
Connect with a community of local professionals.
Explore All Events
IBM is the latest notable tech firm to affirm its commitment to the local quantum scene.
Startups going through Duality, the nation's first quantum startup accelerator, will now get access to IBM's quantum network along with additional support and resources from the tech giant.
READ MORE: IBM expands support for Chicago's quantum startups
More Chicago Inno news to know
The University of Chicago is partnering with Alchemist Accelerator — an institution out of California's Bay Area that's raised $4B and supported more than 650 companies — to help bring more local scientific breakthroughs from lab to market.
is partnering with — an institution out of California's Bay Area that's raised $4B and supported more than 650 companies — to help bring more local scientific breakthroughs from lab to market. The Department of Labor is expanding the number of small businesses that could see big cuts in their Occupational Health and Safety Administration fines.
is expanding the number of small businesses that could see big cuts in their Occupational Health and Safety Administration fines. Bonsai announced an investment of $1.8M to accelerate go-to-market efforts for its marketing intelligence platform.
Infleqtion to build advanced quantum computer in Chicago
A new public-private partnership will make Illinois home to one of the most advanced quantum platforms in the world, the state announced Wednesday.
As part of an expected $50M investment over the next four years, quantum startup Infleqtion plans to build the first utility-scale neutral atom quantum computer at the Illinois Quantum and Microelectronics Park on Chicago's South Side. Infleqtion will work in partnership with the quantum park and the National Quantum Algorithms Center.
READ MORE: Infleqtion to build advanced quantum computer in Chicago as part of $50M investment
Sign up for Inno's free twice-weekly newsletter to receive the latest innovation news impacting Chicago
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
USA Today
an hour ago
- USA Today
MCP Connects, SDP Delivers: The Missing Half of AI Memory is Here
Prescott, Arizona / Syndication Cloud / July 22, 2025 / David Bynon Key Takeaways Model Context Protocol (MCP) creates AI connections to external tools but doesn't define structured memory content Semantic Digest Protocol (SDP) provides trust-scored, fragment-level memory objects for reliable AI operations Multi-agent systems typically fail due to missing shared, verifiable context rather than communication issues MCP and SDP together form a complete memory architecture that stops hallucinations and contextual drift MedicareWire will implement SDP in 2025 as the first major deployment of AI-readable, trust-verified memory in a regulated domain AI's Memory Crisis: Why Today's Systems Can't Remember What Matters Today's AI systems face a critical problem: they process vast information but struggle with reliable memory. This isn't merely a technical issue — it's what causes hallucinations, inconsistency, and unreliability in advanced AI deployments. This problem becomes obvious in multi-agent systems. When specialized AI agents work together, they don't typically fail from poor communication. They fail because they lack shared, scoped, and verifiable context. Without standardized memory architecture, agents lose alignment, reference inconsistent information, and produce unreliable results. David Bynon, founder at MedicareWire, identified this issue early on. In regulated areas like Medicare, incorrect information can seriously impact consumers making healthcare decisions. The solution needs two protocols working together to create a complete memory system for AI. The first protocol, Model Context Protocol (MCP), addresses the connection problem. But it's just half of what's needed for truly reliable AI memory. Understanding Model Context Protocol (MCP) IBM recently recognized the Model Context Protocol (MCP) as core infrastructure for AI systems, describing it as 'USB-C for AI' — a universal connector standard allowing AI models to connect with external tools, data sources, and memory systems. This recognition confirmed what many AI engineers already understood: standardized connections between AI models and external resources build reliable systems at scale. IBM's Recognition: The 'USB-C for AI' Breakthrough The USB-C comparison makes sense. Before USB standardization, connecting devices to computers required numerous proprietary ports and cables. Before MCP, every AI tool integration needed custom code, fragile connections, and ongoing maintenance. IBM's official support of MCP acknowledged that AI's future requires standardized interfaces. Just as USB-C connects any compatible device to any compatible port, MCP creates a standard protocol for AI systems to interact with external tools and data sources. What MCP Solves: The Transport Problem MCP handles the transport problem in AI systems. It standardizes how an AI agent: Negotiates with external systems about needed information Creates secure, reliable connections to tools and data sources Exchanges information in predictable, consistent formats Maintains state across interactions with various resources This standardization allows developers to build tools once for use with any MCP-compliant AI system. Custom integrations for each new model or tool become unnecessary — just consistent connectivity across platforms. The Critical Gap: Missing Content Definition Despite its value, MCP has a major limitation: it defines how AI systems connect, but not what the content should look like. This resembles standardizing a USB port without defining the data format flowing through it. This creates a significant gap in AI memory architecture. While MCP handles connections, it doesn't address: How to structure memory for machine understanding How to encode and verify trust and provenance How to scope and contextualize content How information fragments should relate to each other This explains why AI systems with excellent tool integration still struggle with reliable memory — they have connections but lack content structure for trustworthy recall. Semantic Digest Protocol: The Memory Layer MCP Needs This is where the Semantic Digest Protocol (SDP) fits — built to work with MCP while solving what it leaves unaddressed: defining what memory should actually look like. Trust-Scored Fragment-Level Memory Architecture SDP organizes memory at the fragment level, instead of treating entire documents as single information units. Each fragment — a fact, definition, statistic, or constraint — exists as an independent memory object with its own metadata. These memory objects contain: The actual information content A trust score based on source credibility Complete provenance data showing information origin Scope parameters showing where and when the information applies Contextual relationships to other memory fragments This detailed approach fixes a basic problem: AI systems must know not just what a fact is, but how much to trust it, where it came from, when it applies, and how it connects to other information. Using the 'USB-C for AI' analogy, SDP is a universal, USB-C thumb drive for the Model Context Protocol. It provides data, across multiple surfaces, in a format MCP recognizes and understands Machine-Ingestible Templates in Multiple Formats SDP creates a complete trust payload system with templates in multiple formats: JSON-LD for structured data interchange TTL (Turtle) for RDF graph representations Markdown for lightweight documentation HTML templates for web publication Invented by David Bynon as a solution for MedicareWire, the format flexibility makes SDP work immediately with existing systems while adding the necessary trust layer. For regulated sectors like healthcare, where MedicareWire operates, this trust layer changes AI interactions from educated guesses to verified responses. The Complete AI Memory Loop: MCP + SDP in Action When MCP and SDP work together, they form a complete memory architecture for AI systems. Here's the workflow: From User Query to Trust-Verified Response The process starts with a user query. Example: 'What's the Maximum Out-of-Pocket limit for this Medicare Advantage plan in Los Angeles?' The AI model uses MCP to negotiate context with external resources. It identifies what specific plan information it needs and establishes connections to retrieve that data. The external resource sends back an SDP-formatted response with the requested information. This includes the MOOP value, geographic scope (Los Angeles County), temporal validity (2025), and provenance (directly from CMS data), all with appropriate trust scores. With trust-verified information, the model answers accurately: 'The 2025 Maximum Out-of-Pocket limit for this plan in Los Angeles County is $4,200, according to CMS data.' No hallucination. No vague references. No outdated information. Just verified, scoped, trust-scored memory through standardized connections. Eliminating Hallucinations Through Verified Memory This method addresses what causes hallucinations in AI systems. Rather than relying on statistical patterns from training, the AI retrieves specific, verified information with full context about reliability and applicability. When information changes, there's no need to retrain the model. The external memory layer updates, and the AI immediately accesses new information—complete with trust scoring and provenance tracking. Real-World Implementation: MedicareWire 2025 This isn't theoretical — SDP launches on in August 2025, marking the first major implementation of AI-readable, trust-scored memory in a regulated domain. 1. First Large-Scale Deployment in a Regulated Domain The healthcare industry, especially Medicare, offers an ideal testing ground for trust-verified AI memory. Incorrect information has serious consequences, regulations are complex, and consumers need reliable guidance through a confusing system. MedicareWire's implementation will give AI systems unprecedented accuracy when accessing Medicare plan information. Instead of using potentially outdated training data, AI systems can query MedicareWire's SDP-enabled content for current, verified information about Medicare plans, benefits, and regulations. 2. Solving Healthcare's Critical Information Accuracy Problem Consumers using AI assistants for Medicare options will get consistent, accurate information regardless of which system they use. The SDP implementation ensures any AI agent can retrieve precise details about: Plan coverage specifications Geographic availability Cost structures and limitations Enrollment periods and deadlines Regulatory requirements and exceptions All come with proper attribution, scope, and trust scoring. 3. Creating the Foundation for Multi-Agent Trust Infrastructure Beyond immediate benefits for Medicare consumers, this implementation creates a blueprint for trust infrastructure in other regulated fields. Multi-agent systems will have shared, verifiable context — eliminating drift and hallucination problems that affect complex AI deployments. The combination of MCP's standardized connections and SDP's trust-verified memory builds the foundation for reliable AI systems that can safely operate in highly regulated environments. From Connection to Memory: The Future of Reliable AI Is Here David Bynon, founder of Trust Publishing and architect of SDP, states: 'We didn't just create a format. We created the trust language AI systems can finally understand — and remember.' As AI shapes important decisions in healthcare, finance, legal, and other critical fields, reliable, verifiable memory becomes essential. The MCP+SDP combination shifts from probabilistic guessing to trust-verified information retrieval — defining the next generation of AI applications. SDP will be available as an open protocol for non-directory systems, supporting broad adoption and continued development across the AI ecosystem. As the first major implementation, MedicareWire's deployment marks the beginning of a new phase in trustworthy artificial intelligence. MedicareWire is leading development of trustworthy AI memory systems that help consumers access accurate healthcare information when they need it most. David Bynon 101 W Goodwin St # 2487 Prescott Arizona 86303 United States
Yahoo
3 hours ago
- Yahoo
International Business Machines Corporation (IBM): Don't Abandon The Stock, Warns Jim Cramer
We recently published . International Business Machines Corporation (NYSE:IBM) is one of the stocks Jim Cramer recently discussed. International Business Machines Corporation (NYSE:IBM) is one of Cramer's favorite technology stocks. Throughout this year, the CNBC TV host has expressed optimism about the firm's CEO and the firm's consistency in winning contracts for its enterprise computing business. International Business Machines Corporation (NYSE:IBM)'s shares fell by 7.6% after the firm's latest earnings report saw software revenue of $7.39 billion miss analyst estimates of $7.43 billion. Cramer discussed the earnings report: 'Most of the news is good this morning, IBM. I still think not as bad, uh, Chipotle we have to talk about. Copyright: believeinme33 / 123RF Stock Photo Previously, he discussed potential future International Business Machines Corporation (NYSE:IBM) share price movement: 'Oh, I like IBM very much. I mentioned Ben Wright earlier. I think that Ben, he's really turned me on to this stock. We did a very positive piece about it. I think it goes, I'm going to say not much higher but creeping higher over time, and that's actually a great place to be. So I like IBM.' While we acknowledge the potential of IBM as an investment, our conviction lies in the belief that some AI stocks hold greater promise for delivering higher returns and have limited downside risk. If you are looking for an extremely cheap AI stock that is also a major beneficiary of Trump tariffs and onshoring, see our free report on the . READ NEXT: 30 Stocks That Should Double in 3 Years and 11 Hidden AI Stocks to Buy Right Now. Disclosure: None. This article is originally published at Insider Monkey.
Yahoo
9 hours ago
- Yahoo
IBM Stock Downgraded to $310 Target — But Bank of America Still Says Buy
International Business Machines Corporation (NYSE:IBM) is one of the . On July 24, Bank of America reiterated the stock as 'Buy' and lowered the firm's price target on IBM (IBM) to $310 from $320 following a 'mixed quarter.' The bank said that IBM is well-positioned for growth following its most recent financial report. The company reported adjusted earnings per share of $2.80 for the quarter, beating the LSEG estimate of $2.64. Meanwhile, revenue came in at $16.98 billion, ahead of the expected $16.59 billion. 'IBM reported a mixed quarter, where organic software deceleration was offset by strong contribution from better-than-expected Infrastructure results and higher M & A contribution.' A closeup of a woman's hands typing rapidly on a laptop in a corporate office setting. The firm believes that, post-earnings, IBM has turned into a 'show me' story on software in the second half of the year, but remains bullish on the overall company trajectory. The analysts further stated that they believe estimates will move higher this year and next year, 'with increasing contribution from high-margin software.' International Business Machines Corporation (NYSE:IBM) is a multinational technology company and a pioneer in artificial intelligence, offering AI consulting services and a suite of AI software products. While we acknowledge the potential of IBM 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 best short-term AI stock. READ NEXT: and . Disclosure: None. Sign in to access your portfolio
