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Most large enterprises have already experimented with AI in some form.

They have tested copilots, automated workflows, analytics platforms, content generation tools and customer service assistants, and initial reactions are often positive. Demonstrations create excitement, leadership teams engage quickly and investment follows.

Yet many organizations still struggle to move beyond isolated successes. Adoption slows, usage becomes inconsistent and AI initiatives gradually lose visibility inside day-to-day operations.

What begins as a strategic priority often becomes another innovation program that never fully reshapes the business.

At that point, organizations frequently conclude that the technology is not mature enough.

In reality, the bigger obstacle is often structural rather than technical. AI adoption rarely fails because the tools are incapable.

More commonly, organizations fail to adapt their operating models, incentives and decision-making structures to support meaningful change.

Fragmented ownership weakens adoption

One of the biggest barriers to enterprise AI adoption is unclear accountability: technology teams manage IT infrastructure , governance, security and vendor relationships; innovation teams run pilots; individual business units experiment independently; and senior executives communicate ambition and strategic direction. Yet in many organizations, nobody owns AI adoption from end to end.

But without clear ownership tied to operational outcomes, AI initiatives often become disconnected from how work actually happens. Teams are encouraged to experiment but lack the authority to redesign processes or redefine how decisions are made. Pilots move forward without long-term accountability and successful experiments fail to scale beyond individual departments.

As a result, AI can exist inside the organisation without becoming embedded into its operating model. The technology itself may function well, but adoption stalls because no one is responsible for turning experimentation into lasting behavioral change.

Why technology teams cannot solve this alone

This challenge becomes particularly visible inside platform, data and IT functions. These teams are frequently tasked with enabling enterprise AI adoption by assessing vendors, integrating systems, securing data environments and establishing governance frameworks. At the same time, they are expected to minimize operational risk and ensure compliance requirements are met.

However, they rarely control how individual departments actually work. Technology teams cannot independently redesign sales processes, restructure customer support operations or redefine HR workflows. They can provide tools and infrastructure, but they are not usually empowered to drive organizational change across business functions.

That imbalance creates predictable tension. If AI deployments introduce operational or security risks, technology teams are held accountable. But if adoption slows because departments resist changing established processes, responsibility becomes far less clear.

Over time, this dynamic naturally encourages caution. Teams carrying significant risk without the authority to control it often become more conservative in how aggressively they push transformation initiatives forward.

Incentives matter more than strategy documents

Many organizations also underestimate how strongly incentives shape adoption behavior. A customer service team may be encouraged to use AI tools at the same time as being measured primarily on ticket throughput and response speed. Marketing teams may be asked to experiment with AI-generated content while facing scrutiny over even minor inconsistencies in tone or branding.

Compliance teams could be expected to support innovation even though they’re evaluated almost entirely on risk reduction. In each case, employees respond rationally to the incentives in front of them.

Meaningful AI integration almost always creates short-term disruption. Teams need time to test workflows, adjust processes and learn how humans and AI systems operate together effectively. Productivity can temporarily decline before long-term gains become visible.

If organizations continue rewarding operational stability above all else, employees will avoid experimentation regardless of how ambitious leadership messaging may be.

This is one reason many “AI-first” strategies struggle to move beyond isolated use cases. Declaring strategic intent is relatively easy. Adjusting performance frameworks, redefining accountability and creating room for experimentation is far more difficult.

Unclear governance creates hesitation

Another major obstacle to adoption is uncertainty around governance and operational boundaries. Many organizations still have not clearly defined what AI represents within their broader operating model. Is it an individual productivity layer? A centrally governed capability? A feature embedded into existing enterprise platforms? Or a specialist function managed by dedicated teams? When those questions remain unanswered, ambiguity spreads quickly.

Employees become unsure what usage is permitted, while managers struggle to establish consistent expectations. Technology, legal and compliance teams disagree on where accountability begins and ends - and in practice, this uncertainty often slows adoption more than technical limitations do.

Clear governance does not need to eliminate experimentation. In fact, successful organizations usually balance flexibility with oversight. Employees are far more likely to engage confidently with AI systems when they understand where experimentation is encouraged and where stricter controls apply. Without that clarity, even capable tools can remain underused.

AI transformation is an operational challenge

For CIOs and senior technology leaders, this requires an important shift in perspective. AI transformation is often framed primarily as a technology modernization effort focused on infrastructure, integration and data readiness. Those foundations remain essential. Without them, large-scale deployment is impossible. However, technical readiness alone does not determine adoption outcomes.

The organizations making meaningful progress with AI tend to treat it as an operational redesign challenge rather than simply a software rollout. They integrate AI into existing workflows, align ownership with accountability and adapt governance structures to support new ways of working.

This also explains why many AI programs gradually shift from transformational ambitions into smaller experimental efforts. Experimentation is organizationally safer because it avoids forcing structural change. Unfortunately, it also limits long-term impact.

Successful organizations tend to share several characteristics. They establish clear executive accountability for measurable outcomes linked to AI adoption. Rather than prioritizing short-term stability, they align incentives with workflow evolution. By integrating AI directly into operational systems, they aren’t left to rely on disconnected standalone tools. And they define governance boundaries clearly enough that employees understand how AI should be used.

Notably, none of these are primarily technical decisions. They are organizational and leadership choices.

The real question organizations need to answer

When AI initiatives underperform, organizations often focus first on the technology itself. Vendors are reassessed, models are compared and infrastructure decisions are revisited. Sometimes, those issues do genuinely matter. Often, however, the technology is functioning adequately while the organisation surrounding it has not evolved enough to support adoption at scale.

That distinction is crucial because organizational barriers are solvable. Accountability can be clarified. Incentives can be redesigned. Governance structures can be simplified. Operational ownership can be aligned more effectively with responsibility.

Ultimately, adopting AI means changing how work gets done across the business. And that means the question facing enterprises today is no longer whether AI technology is capable enough to deliver value. It is whether they are prepared to redesign themselves around it.

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San Diego Comic-Con is almost upon us, and fans know that the convention means a lot of entertainment news, celebrity interviews, and perhaps the most exciting part for attendees, Exclusive Merch. The con floor is the hottest place for exclusive releases only available in San Diego from your favorite movies, television shows, comics, and more. Today, Collider is thrilled to partner with Titan Comics to reveal their incredible line-up of over 35 exclusives for fans to get ready for. From Star Wars to a signed Dogma script from Kevin Smith and more, the full list of exclusives available at the Titan Comics booth (#5537) is finally here. We're excited to give you a look at what you can grab!

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Earlier this spring, AMD, Broadcom, Meta, Microsoft, NVIDIA, and OpenAI formed the Optical Compute Interconnect Multi-Source Agreement (OCI MSA) to bring coherence to AI infrastructure and establish a specification for co-packaged optics (CPO) scale-up networks. The architecture they aligned on is a slow and wide non-return-to-zero (NRZ) modulation paired with wavelength-division multiplexing. OCI GEN1 supports four wavelengths at 50 Gbps per channel, delivering 200 Gbps per direction per fiber, and the roadmap scales to 1.6 Tbps per fiber per direction. This consortium settled the architectural debate over the direction of networking in AI. The specification defines the first step in the architecture, but leaves the harder question open: How bandwidth continues to scale, and what comes after four wavelengths. The roadmap calls for adding wavelengths on the same fiber infrastructure to grow bandwidth, but does not specify which manufacturing approach will deliver them. The road to more wavelengths is the answer First-movers have already settled this argument. The OCI MSA's founding members endorsed four wavelengths as the GEN1 starting point, Ayar Labs has been on the eight-to-16 wavelength path for years, and NVIDIA's published roadmap, "A Roadmap Toward Sub-1 pJ/b Optical Interconnect," models a 16-wavelength interconnect as the route to the energy targets the MSA aims at. The decision to use slow-and-wide is an energy-per-bit argument. Low symbol rates and simple encoding go together: NRZ carries one bit per symbol, while PAM-4 carries two but requires roughly three times the optical power to hit the same bit-error rate (BER). NRZ holds BER low enough that forward error correction (FEC) stays light, latency remains tight and predictable, and the link stays within its energy budget. On the electrical side, SerDes power per bit at 50 GBaud is roughly one-third that at 100 GBaud. That regime must be preserved as bandwidth scales, or it can be walked back. Wavelength multiplication keeps the link inside the slow-and-wide regime, whereas symbol-rate escalation walks the architecture back out of it. For readers who want the underlying physics, see "Why 'Optics When You Must' is Now." The industry can now treat increasing wavelength count as settled and turn to the next problem: Manufacturing stable precision laser arrays in massive quantities. Three eras of photonic integration Photonic integration has evolved through three manufacturing eras. Each was driven by the same forces that drove every transition in the semiconductor industry: Lower cost, higher reliability, and industrial-volume scale. The first was the discrete optical assembly era. Components were made separately from exotic materials, precisely aligned by hand, and packaged individually. Expanding system capabilities meant more components and more assembly steps, and every fiber attachment was a costly potential failure point. The cost curve was flat by construction, or even negative, as yields fell. The second era was silicon photonics. Components, including modulators, waveguides, and photodetectors, moved onto a single monolithic wafer, so a portion of the photonic stack could achieve the cost curves of the semiconductor process. Instead of scaling with assembly capacity, the silicon portion could scale by running more wafers on a single flow. The breakthrough was real but incomplete, because critical components could not be integrated. The stubborn, non-silicon III-V gain material was the holdout, and the cost curve remained partial: A high-volume foundry process bolted to a discrete-component bottleneck at the most demanding interface. The foundry flow excluded lasers, semiconductor optical amplifiers (SOA), and high-speed modulators. The third era, heterogeneous integration of all photonic materials on a single wafer, has finally arrived. Combining III-V gain material with silicon photonics brings lasers, semiconductor optical amplifiers, and high-speed modulators into a single wafer-level process. The complete photonics signal chain consolidates on the wafer, and the gain material becomes just another step in a wafer process-flow cost curve, with wafer-level cost, scale, and reliability. The trend towards ever-increasing integration is inevitable. It is the manufacturing transition CMOS underwent in electronics: A single, elegant process that absorbed new device types, compounded over generations at massive scale, and became the foundation for the modern semiconductor industry. Photonics is repeating it, just in time for the massive deployment in AI datacenters. The wavelength staircase The OCI GEN1 specification is four wavelengths at 50 Gbps NRZ, delivering 200 Gbps per fiber in each direction, with MSA channel spacing of 400 GHz. It serves as a practical starting point: Sufficient to demonstrate the architecture in production silicon and coordinate the supply chain, but not enough to support the next generation of GPUs, which will require higher bandwidth per fiber. OCI GEN1 sets the first minimum multi-wavelength standard, not the maximum. Each step up the staircase runs slow and wide, so the per-channel electronics do not change. The dense wavelength-division multiplexing (DWDM) step occurs at wavelengths of eight or more, where channel spacing tightens. System-level bandwidth scales with the number of wavelengths: More lanes, more rings, no change in per-channel design effort. Doubling the wavelengths doubles the bandwidth without doubling the design cost. Eight wavelengths deliver 400 Gbps per fiber per direction, and 16 deliver 800. Bidirectional transmission over the same fiber further reduces the fiber count, and none of it requires faster SerDes, deeper FEC, or PAM-4 power and latency penalties. Wavelengths bend the cost curve for per-fiber bandwidth and enable scale-up domains to grow from tens of GPUs today to thousands tomorrow. Multiplexing at the laser source prevents fiber-count growth, so the number of fibers per connector doesn't explode as the wavelength count rises. The bigger payoff is what cluster size unlocks, rather than raw throughput. Larger, flatter, low-latency scale-up domains enlarge working memory, extend the context window, and add transformer layers, which together support deeper reasoning, fewer network stalls, and higher GPU utilization. Today's wavelength-count decision sets the ceiling on which models the resulting cluster can run in 2028 and beyond. That gives system architects a sixth metric alongside energy per bit, latency, per-fiber throughput, and reach: Wavelength-scaling headroom on the same manufacturing flow. The question to ask is whether the supplier's light-source architecture extends to eight, 16, and beyond without re-engineering. Where the answer is no, the redesign is already on the calendar, with a two-year delta baked in. Manufacturing decides the curve The OCI MSA roadmap to 1.6 Tbps per direction per fiber is achievable on paper. The harder question is which manufacturing approach gets the industry there. Discrete-laser supply chains were not built for hyperscale volumes, and the two structural paths hit the same wall by different routes. The shared-laser path combines multiple lasers through a combiner-and-splitter network to feed a multi-wavelength source. Splitting losses scale with channel count: Every additional output tapped off the network costs the laser optical power it has to make up at the input. Each laser pushes harder to maintain budget across more channels, drive currents climb, and reliability margins erode at every wavelength step. The economics that work at four wavelengths do not extend to eight, let alone 16. The dedicated-laser path uses one laser per wavelength, and assembly complexity scales linearly with channel count when multiplexing with discrete optics. A single module supplying 16 wavelengths across eight fibers would result in roughly 128 lasers, 128 fiber alignments, and 128 monitoring photodiodes. Each alignment has to hold to micrometre tolerances across temperature swings, package stress, and years of field life, and failure-rate math compounds at every interface. Volume is the binding constraint. Hyperscale CPO will need millions of laser-source units per month, not tens of thousands, and discrete-laser approaches do not extend to those volumes regardless of which path is taken. This, rather than the architectural debate, is what has held DWDM back as a deployable architecture. The architectural debate was always going to settle here; the supply chain was not. Once the next wavelength is no longer a discrete-component assembly step but becomes another circuit element on the silicon photonics wafer, the cost of adding wavelengths follows a semiconductor learning curve. Heterogeneous integration provides that curve, and the OCI roadmap requires it. The CMOs of photonics Heterogeneous integration is the manufacturing pattern that closes the integration gap silicon photonics has carried since its inception. III-V gain materials, modulators, photodetectors, and waveguides come together in a single wafer-level flow. This is what CMOS did for electronics. CMOS established a single industrial process that absorbed transistor types, then logic, then memory, and eventually larger functional families, all within the same foundry flow. Each new device family inherited the process's cost curve rather than starting its own, and that inheritance is what lets CMOS compound over generations: Every advance in the underlying process improves every device built on it. The free ride came from the manufacturing pattern, not from the transistor. SHIP™, Scintil Heterogeneous Integrated Photonics, is the equivalent pattern for photonic device integration. The claim is pattern equivalence, not scale equivalence: Photonics is repeating CMOS as a manufacturing transition, not as a market size. The pattern is already running. SHIP™ sits on Tower Semiconductor's silicon photonics platform on 200 mm production lines today, the same lines that turn out tens of millions of pluggable optical transceivers. The 300 mm path is next. The platform is already reaching beyond the laser source. At OFC 2026, four architecturally distinct system vendors independently requested SHIP™ extensions, each pursuing a different system goal: Deeper transceiver integration, advanced optical switching, high-speed modulation at scale, and integrated amplification architectures. Each needed the same underlying capability: III-V integration into the silicon photonics flow, for optical amplifiers and high-speed modulators that pure silicon cannot deliver. None of them was solving the same problem, and the common factor was the manufacturing pattern, not the device. What comes after the first generation Two generations from now, the scale-up fabric is a multi-rack signal chain that binds thousands of GPUs into a single coherent compute domain. The fiber plant that carried four wavelengths also carries 16, then the next, without rework. Lasers, modulators, photodetectors, and optical amplifiers are circuit elements on the silicon photonics wafer, not parts assembled into modules. The interconnect ceases to be an assembly problem and becomes a process-node problem. Power per bit decreases as the signal chain no longer crosses fiber interfaces and material boundaries, and bandwidth at the package edge rises with integration density. The teams designing for that architecture today will hold the architectural position when it becomes the default. The teams that defer the manufacturing question will spend two generations rebuilding programs around suppliers who solved it earlier. LEAF Light™ is the production proof: A single-chip DWDM-native light engine, demonstrated in eight- and 16-wavelength configurations compatible with microring-based CPO transceivers and manufactured on established production lines. Scintil's Series B included participation from NVIDIA as part of broader ecosystem alignment. The OCI MSA settled the architecture. The path to ship it runs through heterogeneous integration. Matt Crowley is the CEO of Scintil Photonics. Contributed by OmniScale Media.

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The past 250 years of optical telescopes have seen revolutionary discoveries and technology that the telescope's inventor, a seventeenth century spectacle-maker by the name of Hans Lippershey, maybe wouldn't have believed possible.

When we look back through the annals of telescope history, we find that a significant turning point came, coincidentally, just five years after the United States' Declaration of Independence was christened.

It was back in England, in 1781. William Herschel had just made what was possibly the greatest astronomical discovery the world had seen up to that point: a new planet, Uranus . The fact that Herschel had found a seventh planet from the sun was revolutionary in itself. All the other planets, from Mercury to Saturn , had been known since antiquity, obvious in the night sky to the naked eye.

Uranus, on the other hand, isn't really visible without optical aid, and its discovery illustrated the power of the telescope to dramatically widen our vistas. Moreover, Herschel found the new planet using a 6.2-inch (157-millimeter) reflecting telescope that he had constructed himself. He was looking through it from the back garden of his home in the Somerset city of Bath.

Herschel was a prolific builder of telescopes, polishing and shaping their speculum mirrors. The 6.2-inch telescope was a midget compared to some of his other beasts, including the famous discovery machine that was the 20-foot, or -meter, in focal length telescope with its 18-inch (457-mm) aperture, and the less successful 40-foot (12-meter) telescope.

Herschel proved that telescopes could do serious science. "As a self-taught astronomer, William Herschel transformed the reflecting telescope from what had generally been thought of as a scientific toy into a serious scientific tool," British science historian Robert Smith of the University of Alberta in Canada told Space.com. "At the root of all Herschel's efforts is his telescope building, because he had to build these big telescopes himself."

Refractors and reflectors

Telescopes come in two main forms: the reflector and the refractor.

Reflectors use mirrors to reflect light to a focal point where the eyepiece is located; refractors use lenses to focus light. In the 18th and 19th centuries, British reflectors like Herschel's were the dominant telescope category, as exemplified by those constructed by the likes of Liverpool's William Lassell and Ireland's Third Earl of Rosse, William Parsons. However, across the English Channel in mainland Europe, refractors, which at the time were optically higher quality, were dominant instead.

"You have to distinguish what's going on in Britain with what's going on elsewhere," said Smith.

Lassell built reflectors with apertures of 24 and 48 inches (61 and 122 centimeters). And the great Leviathan of Parsonstown in Ireland is Lord Rosse's own behemoth, still standing today as a UNESCO World Heritage Site. While the likes of Lassell and Lord Rosse were wealthy, self-taught "grand amateur" scientists, in Europe refracting telescopes were used by academics at universities to make precise measurements of the cosmos, from the orbits of double stars to the distance to stars using parallax .

The dome of the giant Hooker Telescope. (Image credit: Craig Baker/Wikimedia Commons, CC BY-SA 4.0) "On the European continent, refractors were used by professional astronomers whose focus was on precision, whereas for Lassell and Rosse the focus was on collecting more light to see fainter objects," said Smith.

In comes the U.S.

Building large refracting telescopes had its challenges and led to a period referred to as the "Telescope Race," where prestige was equally a motivation alongside science. The "race" was won by the 40-inch (one-meter) refractor at Yerkes Observatory in Chicago in 1897, which cost $500,000 at the time (about $20 million in today's money ) and was provided by financier Charles Yerkes who made his money developing Chicago's public transport system, often resorting to bribery in order to win franchises.

Businessmen building telescopes was nothing new, of course: William Lassell made fortunes from brewing, but he also used his own telescopes. What was different now was that men wealthy beyond anyone's dreams saw observatories as vanity projects rather than as scientific instruments to use themselves. The introduction of substantial sums of American money provided by wealthy businessmen was a sea change in both the building of telescopes and the fortunes of astronomy in the U.S.

"I have argued that in the 1880s, America was a bit of an astronomical backwater compared to Europe, but by the 1920s the United States had become the leading nation, certainly in terms of observational astronomy," said Smith.

It wasn't just Yerkes. In California, wealthy landowner James Lick founded the Lick Observatory on Mount Hamilton after being dissuaded from his original plan to build a giant pyramid as a monument to himself in downtown San Francisco. Percival Lowell, obsessed with his delusions about canals on Mars , founded the Lowell Observatory in Arizona in 1894. And on Mount Wilson in California, something big was stirring in part thanks to benefactor John Hooker.

Reflectors come of age

Size has always been a driving force, a challenge and a problem for telescope builders. Even today, the Yerkes refractor is still the champion refractor, only rivaled by the one-meter Swedish Solar Telescope on La Palma, but even this is stepped down from 42 inches to 39 inches (107 cm to 99 cm). The issue is twofold: the thicker the lens, the more the incoming light is attenuated and hence the greater the light loss, so you lose any benefits a large lens might provide. Plus, the heavier a lens is, the more it will sag and deform, destroying its ability to focus properly.

This glass ceiling, if you'll pardon the pun, was circumvented by reflecting telescopes following a vital development in the mid-1800s. Herschel and his peers had been using mirrors made from speculum, which is a reflective and slightly toxic (thanks to the small quantities of arsenic added to the copper and tin mix) metal that is prone to tarnishing easily. Herschel had to polish his telescope mirrors frequently to keep them spick and span.

Then in the 1850s scientists Léon Foucault and Carl August von Steinheil figured out a way to add a thin layer of silver to glass, creating mirrors that were much more reflective than speculum, that weighed less and which didn't tarnish. This paved the way for building bigger and better reflectors, fulfilling the promise of the work started by William Herschel.

One key figure in the resurgence of the reflecting telescope around the turn of the 20th century was the astronomical optician George Ritchey, most famous today for being one half of the duo who invented the Ritchey–Chrétien telescope design that is popular with amateur astronomers, particularly planetary imagers, and which is also employed on dozens of professional telescopes including the largest ground-based telescopes currently in operation.

Technicians grinding the 16-foot (five-meter) mirror of the Hale Telescope at Caltech in 1945. (Image credit: Wikimedia Commons) Ritchey had built a 0.6-meter (24-inch) reflector at Yerkes before he was hired by George Ellery Hale, who was the director of Mount Wilson Observatory. On Mount Wilson Ritchey designed a 1.5-meter (60-inch) reflector in 1908 and then what would be the largest telescope in the world at that time, the 2.5-meter (100-inch) Hooker Telescope, made possible thanks to a generous financial gift from John Hooker. The Hooker Telescope saw its first light in 1917.

"If I had to pick one key optician around about 1900, I would pick George Ritchey," said Smith. "Though Ritchey's innovative approach sometimes became too innovative for Hale. Maybe 'firing' is too strong a term, but Ritchey left Mount Wilson because he just didn't get on with Hale."

A revolution in cosmology

Despite the parting of ways, Ritchey's legacy was secure because the Hooker Telescope transformed astronomy and cosmology, thanks to the work of Mount Wilson staff astronomer Edwin Hubble and his colleague and assistant, Milton Humason . Thanks to the sheer resolving power of the Hooker Telescope, Hubble was able to resolve the mysterious spiral nebulae as galaxies in their own right, proving that galaxies other than our Milky Way exist.

He was able to confirm their distance by using the Hooker Telescope to identify individual stars in those galaxies, stars we call Cepheid variables , which have a particular relationship between their period of variation and their peak brightness. The work of Henrietta Swan Leavitt tells us that the longer a Cepheid's period of variability, the brighter they become, and knowing how luminous they should be, Hubble could compare that to how bright they appeared in the night sky through the Hooker Telescope and then deduce how far away they and their galaxies must be. Hubble and Humason later measured the redshifts of these galaxies, finding they are almost all moving away from us and that the cosmos is expanding .

The Hooker Telescope was superseded by the Hale Telescope, named after the Mount Wilson director and which has a 5.1-meter (200-inch) mirror and came into operation on Mount Palomar in 1949. The Hale Telescope remained the largest optical telescope in the world until 1975 and the Soviet Union's six-meter BTA-6 telescope, and this wasn't beaten until 1993 and the construction of the first of the twin 10-meter telescopes of the Keck Observatory on Mauna Kea in Hawaii. At this size, mirrors have to be composed of multiple individual segments rather than being cast as one solid mirror because gravity would otherwise cause the mirror to deform.

During the second half of the twentieth century, astronomers began to identify the best locations for giant optical telescopes, away from the smog and light pollution of cities whose urban sprawl was growing so great that not even Californian mountaintops could escape them. Today, the best telescopes in the world cluster atop Mauna Kea, on numerous peaks in Chile's Atacama Desert, and in the Canary Islands.

How the Hubble Space Telescope democratized astronomy

For the most exceptional views, you can't beat space itself. In orbit above our obscuring atmosphere , or stationed 1 million miles (1.6 million kilometers) away at the L2 Lagrange point , space telescopes enjoy unprecedentedly clear views of the cosmos. The most recent space telescopes include the James Webb Space Telescope and, launching in September, the Nancy Grace Roman Space Telescope , but the most famous of all is of course the Hubble Space Telescope .

Launched in 1990, Hubble continues against all the odds to push the frontiers of science.

"Its output is staggering," said Smith. It has made over 1.7 million individual observations in the past 36 years, and 23,000 research papers based on those observations have been published by a total of nearly 29,000 astronomers.

The Hubble Space Telescope stands tall in the cargo bay of the Space Shuttle Atlantis following its capture and lock-down in Earth orbit. (Image credit: NASA) "This is the democratization of astronomy," said Smith, and it completes a transformation in astronomy over 250 years in the making. Back when the United States was being founded, astronomers were generally lone wolves, self-taught and self-motivated like William Herschel. Then, throughout the nineteenth century astronomy increasingly became the purview of wealthy men, and even moving into the twentieth century, astronomical discovery was confined to a small group.

"For example, in the early 20th century, the only people who had access to the Mount Wilson telescopes were the staff at the Mount Wilson Observatory, and if you were not on staff then you just couldn't use the largest telescopes in the world, so as an observational astronomer you would be at a disadvantage," said Smith.

While this began to change in the latter half of the twentieth century, with organizations such as the European Southern Observatory and the National Optical Astronomy Observatory (now NOIRLab) giving access to telescopes to a wider swathe of people, the Hubble Space Telescope has really spearheaded this democratization.

"People all over the world can use Hubble," said Smith. "It opens up so many possibilities for astronomical research, with thousands of people using it."

From well-heeled enthusiasts to businessmen looking for a legacy, astronomical research has now truly become accessible to people worldwide thanks to the largest telescopes in space and on Earth. Perhaps that is the ultimate achievement of the past 250 years of telescopes.

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VIENNA — Latvia and Ukraine plan to build a joint drone manufacturing facility in the Latgale region of eastern Latvia, near the country’s borders with both Russia and Belarus, Latvian Prime Minister Andris Kulbergs said June 29 during a visit to a military base in the region.

The announcement gives operational shape to the so-called “Drone Deal” signed on June 9 between Kulbergs and Ukrainian President Volodymyr Zelenskyy on the sidelines of the Nordic-Baltic Eight summit in Tallinn, the first meeting between the two leaders. Latvia is the sixth country to join Ukraine’s bilateral drone cooperation framework.

Under the agreement, Ukraine will supply Latvia with strike drones, ground robotic complexes, and maritime drone systems, while Latvia will supply Ukraine with domestically produced anti-drone systems, Ukrainian Defense Minister Mykhailo Fedorov and his Latvian counterpart Raivis Melnis previously confirmed during a meeting in Kyiv on June 13. No specifics were offered.

The Latgale region, where the new drone factory is to be built, is historically one of Latvia’s most economically disadvantaged. Kulbergs said the area needs investment and jobs, and that his government would “do everything necessary” to site the plant near the Russian border. Construction should start this year.

Moscow has been publicly outraged at the Baltic states’ alleged role in Ukraine’s drone warfare against the Russian hinterland, accusing the three small republics of opening their airspaces to Ukrainian drones on their way to strike targets over a thousand kilometers from Kyiv in Russia’s Baltic region and the St. Petersburg area.

More outlandish Russian claims have even included accusations that the Baltic States are allowing Ukraine to launch drones from their territories. The Russian foreign intelligence service SVR, which is renowned for making unsubstantiated and wildly escalatory claims regularly, published a press release with this accusation earlier this year.

The opening of the drone production facility will surely face criticism from Moscow and is all but certain to be seen as an escalatory move. It may also strengthen Russian propaganda’s case for singling out the small Baltic states as particularly hostile − and a particularly urgent problem − for Moscow.

Key details − including the plant’s precise location, cost-sharing arrangements between Riga and Kyiv, and which drone types will be produced − have not been publicly disclosed.

In addition to the joint drone factory, the Latvian prime minister also announced that counter-drone systems will begin operating along Latvia’s borders with Russia and Belarus in July and August − removing the need, he said, to scramble fighter aircraft in response to every drone incursion. “In the event of a threat from drones, we won’t have to take aircraft into the air every time, which is a very expensive and effective solution, but not the best and most productive,” Kulbergs said.

A top Latvian official previously described to Defense News a system of launch canisters stationed along the border.

Yesterday’s announcement comes against a fraught political backdrop in Riga. A suspected stray Ukrainian drone that entered Latvian airspace from Russia exploded at an oil storage facility in Rēzekne on May 7, damaging four empty fuel tanks. The incident triggered the resignation of both the defense minister and Prime Minister Evika Siliņa within days. Kulbergs took office shortly thereafter.

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One of the many millions of people captured by the Romans and sold into slavery was a man who died in Ravenna in the 1st century BC. He wrote his own story, on his own tombstone, so that everyone who saw it would know what he endured and what he survived.

Gaius Julius Mygdonius, Parthian in origin. Born a free man and captured as a boy, given away to Roman territory. When helpful fate made me a Roman citizen, I began to save for when I became 50 years old. Ever since my youth I have wanted to reach my old age. Now, stone, receive me willingly; with you I shall be released from my worries.

Gaius Julius Mygdonius wasn’t the name he was given by his father, and it wasn’t the name he bore when the Romans captured him, nor was it the name he was called on his travels to Italy or during his life in slavery. At some point he became merely Mygdonius to his captors and his enslavers, which simply denotes him as a person from Mygdonia (Bulgaria and northern Greece). Mygdonius describes himself as a Parthian, which means he was from ancient Persia.

We know that he was captured as a child after experiencing the Roman war, and possibly a Roman siege. Eyewitness accounts of the Roman war terrify even across a few thousand years of distance. When the Romans breached the walls of a city, they killed, indiscriminately, everyone they came across, following their orders to “kill all they came across, sparing none, and to not start pillaging until the signal was given.” Bodies filled the streets. Not just of humans, but of dogs and horses cut in half, says the Greek historian Polybius, who was himself taken captive in a Roman assault. The soldiers raped and killed until they were exhausted.

We have two eyewitness accounts of the process of being taken as a captive by the Romans. Neither is by someone who was himself enslaved, because both were too noble for slavery. They are non-Roman witnesses to Roman war. The first comes from the works of Polybius, a Greek statesman from the fantastically named city of Megalopolis who ended up first a captive in Rome following the Third Macedonian War in 168 BC, and then a tutor to Scipio Aemilianus. When Scipio grew up and became the leading general in the third war against Carthage, he took Polybius along with him — rather against Polybius’ will — and Polybius eventually wrote an account of what he saw during this time. The second account comes from Josephus, a Jewish scholar and leader born Yosef ben Matittyahu in Galilee who fought against the Romans in the Jewish War and was taken captive after the brutal siege of Yodfat in 67 AD. He accompanied the emperors Vespasian and Titus for the rest of the war until the sack of Jerusalem and the destruction of the Second Temple in 70 AD. Titus then took him back to Rome, where he developed a nice line in explaining Jewish history to the Romans and Roman history to the Jews.

Both Polybius and Josephus wrote accounts of the Roman process of taking and organizing their captives following a battle or siege and, although they were written 200 years apart, they are remarkably consistent. For a start, the life stories of both men provide useful examples that show that it was not local elites who were being enslaved by the Romans. Status protected people in captivity as it did in life, and no Macedonian or Bithynian leader ever ended up chained in a field in Sicily. The people who the Romans took captive and enslaved were the poor, the workers, and the already enslaved.

Mygdonius was one of these non-elites who survived the Roman onslaught. Still breathing when the signal came to stop the slaughter and start the pillage, Mygdonius became booty. Rounded up from his hiding place by a towering, battle-scarred soldier of Rome, he then waited to find out his fate. After hours, maybe days, of waiting the commander appeared to divide his captives; a tedious administrative job for a Roman general, but for Mygdonius and his fellow captives, perhaps the most important day of their lives. Would they be executed or enslaved? Would the general allow them to be ransomed, and was there anyone to ransom them?

Mygdonius was too lowly to be ransomed or taken into a relatively luxurious prison as a hostage, a fate open only to those blessed with noble blood. The choices facing him were death or slavery, and he was granted slavery. The Roman lawyers believed that slaves were called servi because generals saved ( servare ) them from death and so it was with Mygdonius. He was not given to the soldiers as a prize, or sent into public slavery, or kept as a treat by the general; he was simply sold there and then to the slave traders who followed the Roman army on even the smallest missions to take their booty and turn it into profit.

Both Polybius and Josephus offer detailed breakdowns of individual sieges and the aftermath in which the huddled, terrified inhabitants of cities were divided up into categories and sent off to new lives. Polybius describes the short and (relatively) uneventful siege of New Carthage (Cartagena, Spain) in 209 BC. Scipio took the city in a matter of days and without much struggle but still “as is the Roman custom” sent his troops to slaughter the population without mercy, dismembering not just the people but also their animals and burning their homes until they had the New Carthaginian general in custody. This worked pretty fast because, well, it would. Start cutting a person’s children and dogs in half in front of them and they do tend to despair.

Within a few hours Scipio had accepted the unconditional surrender of his New Carthaginian counterpart. The next day, he set to dividing up the booty, including the 10,000 prisoners. First, says Polybius, Scipio removed the political men with their wives and children and, asking them to look kindly on the Romans, he let them go free. This act of clemency was extended only to the city’s political elite.

The next group to be identified were the craftsmen or artisans, people like stonemasons and carpenters. These 2,000 men he made slaves of the Roman Republic, publicly owned to ply their trade for the good of their enemy. Then, Scipio picked out the strongest young men and condemned them to serve in the Roman navy as oarsmen. He also promised these men that if they helped him win the war and didn’t, y’know, die in hideous ancient naval battle or drown in the Mediterranean, he would free them when it was all over. All the rest of the prisoners, he handed over to the proper officials to be sold to the dealers who followed the armies. Polybius recorded these details because he believed Scipio to be uniquely merciful and moderate and to have generally demonstrated that the Romans were a great bunch of lads. The fates of the men, women, and children who were stripped, eyeballed, and sold on the auction block were of no more interest to him than the fates of the individual silver coins taken from the city’s treasury. They were merchandise now to be dealt with as property, not people.

As Cicero finished a minor campaign in Cilicia, he wrote a long letter to his bestie Atticus describing his adventures and finished up by saying that the only plunder he had kept for himself were the captives being sold at that moment. “As I write, I have 120,000 sesterces on the block,” he said, reducing all those poor people to cold cash and naked bodies.

The fates of the men, women, and children who were stripped, eyeballed, and sold on the auction block were of no more interest to [Scipio] than the fates of the individual silver coins taken from the city’s treasury.

Josephus describes pretty much the exact same process happening in Judea in 69 AD. There, the Roman generals were less interested in winning the goodwill of the population they had defeated and so Josephus claims that, in total, the Roman army took 97,000 people into slavery in the Jewish War, which is more people than can fit in Wembley Stadium. He describes Vespasian dividing up the captives at Tarichaea in Galilee, executing 1,200 of the elites, sending 6,000 of the strongest young men to dig Nero’s folly of a canal in Greece, and selling 30,400 people on the auction block.

These numbers blur. They are simply too big to conceptualize as individuals: 30,400 Mygdoniuses; 30,400 of your child, your mum, your brother; 30,400 human beings.

A year later, after the sack of Jerusalem, the Roman general decided to divide the captives up by age and looks: “He selected the tallest and most handsome of the youth and reserved them for the triumph; of the rest, those over 17 years of age he sent in chains to the works in Egypt, while multitudes were presented by Titus to the various provinces to be destroyed in the theaters by the sword or by wild beasts; those under seventeen were sold.” Very few of these would ever know freedom again; most would die hideously. Every one of them would be chained by the neck and ankle and wrist and led on nightmare journeys across deadly seas to foreign places. Every one of them would be beaten, at least as part of the process of making a free person realize that they were no longer a person, of turning a human into a slave.

Thus, with thousands of others, Mygdonius was chained at the neck and the leg, the cold metal resting heavily on his collarbone, chafing at his ankle, rubbing his skin raw and red. We see how enslaved people moved across the empire in the tombstone of Aulos Kapreilios Thimotheos, a dealer in slaves who had a line of eight chained men carved into his 2-meter-high memorial. This was the first step in Mygdonius’ transformation from a person into a slave, a life which hung between life and death. Maybe he thought about escaping, maybe he thought about suicide as he walked from the city to the sea, and then endured the Mediterranean crossing. Many, many men and women killed themselves on the boats to escape the violence and humiliation they knew lay ahead of them.

But Mygdonius always had hope. He says so himself. “Ever since I was young, I have wanted to reach my old age.” Captured as a child, Mygdonius clung to the dream of survival. Through his sale into imperial slavery, through the erasure of his old self and the creation of a new person: Mygdonius, the slave known only by his place of origin. Through his grinding years of enslavement, and his tireless work that finally led to his being freed. Through his third renaming, taking on Gaius Julius, the names of the people who enslaved him. Through it all, he remained a free Parthian in his heart. He saved and saved and worked and saved so that when he died, in his old age, his ashes could be interred in a huge sarcophagus of marble and the important facts of who he really was — free, freed, rejecting the slavery that sought to erase him — could be proclaimed forever to all who passed by.

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Credit: Ryan Haines / Android Authority

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Pixel owners are reporting a strange popping sound when using their devices.

Some claim that the popping happens randomly, while others say it occurs when switching apps or playing games.

Disabling Adaptive Sound appears to have helped some affected users.

Imagine you’re on your phone playing a game, and out of nowhere, you hear a popping sound come from the audio. That would be pretty distracting, if not annoying, right? Now, imagine that inexplicable sound is triggered whenever you use your phone. That’s the problem some people are currently experiencing with their Pixel phone.

Pixel owners have started noticing a popping/clicking sound while using the handset. According to reports on Reddit , the popping sound happens randomly for some. Others claim that the popping is triggered by a specific action, such as switching between apps or playing certain games.