Better Your Tech

10/05/2026

Juat a shame 😶

Final.

09/30/2026

A lot has happened this year… including getting married ❤️
We took some time to enjoy life, travel, reset, and get clear on what comes next.
It’s been a good reminder to slow down when it matters, enjoy the moment, and come back with a clearer direction.
Now it’s time to put the next part of the plan into motion.

04/22/2026

Tech News 🚀 | AI Infrastructure

Meta expanded its partnership with CoreWeave through a new $21 billion agreement for additional AI cloud capacity, adding to a prior $14.2 billion deal signed in September. The new contract runs through December 2032 and deepens Meta’s long-term infrastructure commitment.

This matters because the agreement gives Meta access to some of the initial deployments of Nvidia’s Vera Rubin platform, showing how leading AI companies are locking in compute years in advance. It also reinforces how cloud capacity is becoming a strategic asset in the race to build and deploy large-scale AI systems.

Long term, the companies with the strongest access to advanced chips, cloud infrastructure, and durable compute contracts may hold the biggest advantage in enterprise AI.

What will define AI leadership more over the next decade: better models or better infrastructure?

— BYT

04/21/2026

Tech News 🚀 | AI Infrastructure

Meta has extended its Broadcom partnership through 2029 to develop multiple generations of custom AI chips as it expands compute capacity for AI services across its platforms. Reuters reported that the first phase includes more than one gigawatt of capacity, with broader scaling planned beyond that.

This matters because hyperscalers are pushing further into custom silicon to reduce dependence on third-party GPU supply, improve efficiency, and optimize infrastructure for large-scale AI workloads. Reuters also reported that Broadcom’s Ethernet networking hardware will connect Meta’s growing AI infrastructure, underscoring that the competitive edge now spans chips and network architecture together.

Long term, AI leadership may depend less on access to models alone and more on owning the infrastructure stack behind deployment at scale.

Which will matter more over the next five years: proprietary models or proprietary infrastructure?

— BYT

04/20/2026

Tech News 🚀 | AI Infrastructure

Meta has extended its Broadcom partnership through 2029 to develop multiple generations of custom AI chips as it scales compute capacity for AI services across its platforms. The agreement also includes Broadcom networking hardware, with the first phase delivering more than one gigawatt of capacity.

This matters because hyperscalers are moving deeper into custom silicon to reduce reliance on third-party GPU supply, improve cost efficiency, and tune infrastructure for inference-heavy workloads. Reuters also reports that cloud giants are expected to spend more than $600 billion on data centers in 2026, reinforcing how central chips and networking have become to enterprise AI competition.

Long term, the advantage in AI may come less from model access alone and more from controlling the infrastructure stack behind deployment.

Which will define the next phase of AI leadership more: proprietary models or proprietary infrastructure?

— BYT

04/16/2026

Tech News 🚀 | Semiconductors

TSMC raised its 2026 revenue outlook and increased capital spending as demand for AI chips remained exceptionally strong. The company also projected second-quarter revenue well above the same period last year.

This matters because TSMC sits at the center of the global AI supply chain, manufacturing advanced chips for many of the industry's most important players. Stronger guidance signals that AI infrastructure demand is still expanding at scale.

Long term, sustained spending at the foundry level suggests the AI buildout is becoming a durable industrial cycle, not a short-lived surge.

What does stronger foundry demand tell you about the next phase of AI infrastructure?

— BYT

04/14/2026

Tech News 🚀 | AI Infrastructure

Meta expanded its AI cloud partnership with CoreWeave with a fresh $21 billion deal for additional compute capacity. The agreement runs through December 2032 and adds to a prior $14.2 billion agreement signed in September.

This matters because the deal gives Meta access to early deployments of Nvidia’s Vera Rubin chips, while reinforcing how AI development is pushing hyperscalers and neocloud providers to lock in massive infrastructure commitments years in advance.

Long term, this signals that competitive advantage in AI will depend as much on secured compute, cloud capacity, and advanced chip access as on model design itself.

Which will matter more over the next five years: proprietary models or proprietary infrastructure?

— BYT

04/13/2026

Tech News 🚀 | Semiconductors

Global semiconductor supply constraints continue to pressure fabrication capacity, as demand across AI, automotive, and cloud infrastructure outpaces production output.

The imbalance is exposing structural weaknesses in supply chains, with limited advanced-node capacity and geographic concentration creating persistent bottlenecks.

Long-term, this accelerates national investments in domestic chip manufacturing and supply chain diversification.

What part of the semiconductor supply chain do you think is most vulnerable today?

— BYT

04/11/2026

Tech savvy friends, let's vibe safe! Protect your online info, think before you post, and share those happy moments... ⚠️

04/10/2026

Tech News 🚀 | Quantum Computing

A major advance in quantum processors is pushing the field closer to practical, large-scale performance. The latest development signals continued progress in chip design, system stability, and computational reliability.

It matters because quantum hardware progress is no longer just theoretical research. Each processor milestone improves the case for enterprise experimentation in optimization, simulation, and next-generation compute infrastructure.

Long term, stronger quantum processors could reshape how critical industries approach high-complexity workloads.

What would need to happen next for quantum systems to become commercially useful at scale?

— BYT