My New Lawfare Article on "Why Callais Doesn't Justify Court-Packing"
Court-packing would cause great harm, including by boosting power-grabbing presidents like Trump. Callais's flaws are better addressed by other means.
๐บ๐ธ ๋ฏธ๊ตญ ยท "JUSTIFY" ยท ์ด 24๊ฑด
ํํฐ ๋ณด๊ธฐํ์ฌ ์ง์
48.8
0 = ๋ถ์ ์ฐ์ธ
50 = ์ค๋ฆฝ
100 = ๊ธ์ ์ฐ์ธ
์ต๊ทผ 7์ผ ๊ธฐ์ค 11,084๊ฑด์ ๋ถ์ํ ๊ฒฐ๊ณผ, ๋ด์ค ์ฌ๋ฆฌ์ง์๋ 48.8(๊ท ํ)์ ๋๋ค. ๊ธ์ 1,115๊ฑด(10.1%)ยท์ค๋ฆฝ 7,930๊ฑด(71.5%)ยท๋ถ์ 2,039๊ฑด(18.4%)์ด๋ฉฐ, ์ค๋ฆฝ ๋น์ค์ด ๋๋ ทํ๊ฒ ๋์ต๋๋ค. ์ฑํฅ ์ง์๋ ์ข ํฉ 21.8(๋ณด์ ๊ฒฝํฅ)์ ๋๋ค.
Court-packing would cause great harm, including by boosting power-grabbing presidents like Trump. Callais's flaws are better addressed by other means.
Two members of Congress have sent a letter to US Forest Service Chief Tom Schultz calling on the agency to justify its actions following an investigation by Mother Jones that found glyphosateโthe controversial key ingredient in the herbicide Roundupโwas being sprayed in record amounts on public lands. โGiven the recent scientific disputes, retracted studies, and [โฆ]

An excerpt from Sunar v. Gray Local Media, Inc., decided today by Judge Kenneth Bell (W.D.N.C.): Defendants Gray Local Media,โฆ The post "Desire to Undo the Past" Can't Justify Libel Claim Over "Indisputably Truthful" Articles About Criminal Charges + Expungement appeared first on Reason.com.
Apparently โbecause of woke,โ disparaging a whole community of people based on their nationality and using that sentiment to justify extensive fraud investigations that lead to cutting social services and occupying cities with federal agents is racist. โYouโre not allowed to complain about Somalians because thatโs racist,โ President Donald Trumpโs administrator for Medicare and Medicaid, [โฆ]
the seal of the South Carolina Supreme Court next to a photo of a penile plethysmograph
Cop seemingly ignored Flock camera timestamp to justify arrests.
I spent 16 years planning a World Cup trip with my sons, only to discover we couldn't justify the cost.
None of the recent attacks on the integrity of the Supreme Court are about the rule of law or good social order. They are not being made in good faith.
Agriculture Secretary Brooke Rollins claims "moving the Forest Service closer to the forests we manage is an essential action that will improve our core mission of managing our forests." That is sophistry โ a failed attempt to justify an ill-advised, destructive reorganization plan to remove Forest Service headquarters from Washington and radically cut its research infrastructure. Her fallacy implies that adjacent communities...
Even Russiaโs leading warmonger has run out of ways to justify the Ukraine invasion.
SpaceX's valuation will set the bar for what the must achieve going forward to reward investors.
Making faith a center point of his Senate campaign, James Talarico says he doesnโt want to โclaimโ Jesus for the Democratic Party. Yet the woke church that molded him uses Christ to justify support for abortion, transgender procedures on kids, and protesting immigration enforcement. A review of Talaricoโs Texas church and its activist pastor โ ...
Just when you thought Blake Lively's battle against Justin Baldoni was over, the whole mess has taken a new turn.
This story appeared in The Logoff, a daily newsletter that helps you stay informed about the Trump administration without letting political news take over your life. Subscribe here. Welcome to The Logoff: Donald Trump is still trying to implement his tariff agenda. Wait, didnโt the Supreme Court strike that down? Yes โ this is the Trump administrationโs [โฆ]
Director Kane Parsonsโ horror thriller "Backrooms" opened with an estimated $81 million over the weekend against a $10 million production budget, an amount more than enough to justify the production of at least one sequel.
Jaxson Dart spoke to media after controversy over introducing President Trump at a New York rally, while teammate Abdul Carter publicly criticized his decision.
Sridhar Ramaswamy predicts that companies reliant on seat-based income will scramble to justify their premiums as employees use AI to accomplish an immense amount of work.
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As companies like Meta and Amazon use AI to justify headcount reductions, Costco is doubling down on $1.50 hot dogs and humans at the cash register.
I have been an application-specific IC (ASIC) designer for almost three decades. Over that time, Iโve moved through the full academic trajectory, from graduate student to full professor; later, I transitioned to industry after an unsuccessful stint at entrepreneurship. When I made the switch to the private sector in 2019, I began focusing on a critically important aspect of the electronic industry: silicon intellectual property. As much as 80 percent of the physical area in todayโs most advanced chips is occupied by blocks that arenโt made for specific products or even designed by the consumer-facing companies that built them. Instead, chipmakers draw heavily on established silicon IP from companies like Arm, Cadence, Rambus, Synopsys, and the company I work for, Silicon Creations. Throughout my career, Iโve designed chips for very different purposes, including enabling the research program in my academic lab and expanding the IP portfolio of my company. When I joined Silicon Creations, I had no idea how differently the industry approaches IC design and encountered a steep learning curve. Initially, it seemed that much of my two decades of academic research and training did not directly translate to the role. I had to learn new skills and adopt a new mindset. Today, demand for ASICs is rapidly growing, driven by the need for specialized chips in the automotive sector, AI applications, and more. By one market estimate, the ASIC market is expected to grow from US $23.4 billion to $38.8 billion by 2033, and the semiconductor industry as a whole is projected to hit $1 trillion by 2030. The industry needs more chip designersโbut if youโre coming from an academic background as I did, there are a few things youโll need to know. Different goals lead to different strategies The differences between industry and academe begin with a divergence in purpose. In academia, my primary objective was to generate new knowledge: to propose a novel circuit technique, validate an unconventional architecture, or explore the limits of performance in a given domain. A successful chip is one that demonstrates a concept. In industry, it is not nearly enough to prove that something can work. The goal is to ensure that it works reliably, repeatedly, and at scale. Success is measured not by novelty but by whether the silicon meets specifications, yields as expected in production, and supports a competitive product delivered on schedule. This leads to a stark contrast in risk tolerance. Academic designs often deliberately push into unproven territory, where even partial success can yield valuable insight. In industry, however, we systematically minimize risk. The cost of failure makes first-time silicon success a central requirementโespecially at advanced technology nodes, where the lithography masks used to transfer circuit designs onto silicon wafers alone can cost tens of millions of dollars. As a result, industry design flows are built around eliminating uncertainty through conservative margins, extensive validation, and careful reuse of proven solutions. โAcademia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale.โ This paradigm has existed since the 1970s, when application-specific chip design was established. However, the gulf between academia and industry has expanded since the mid-2010s, when FinFET technology, a 3D architecture using vertical โfinsโ of silicon, was widely adopted in industry. System designs are also becoming increasingly modular with the advent of chiplets. This fundamentally altered the economics and complexity of ASIC development, with design costs rising by almost an order of magnitude. Initiatives like Taiwan Semiconductor Manufacturing Co.โs University FinFET Program and new government-funded chip-design hubs now let some well-resourced universities design for more advanced architectures, but the technology is still out of reach for many academics. What the industry-academia split means in practice Consider a startup developing an ASIC. Its engineering team may have deep expertise in a particular algorithm, sensor interface, or system architecture, the features that define its competitive advantage. But it is unlikely to possess world-class expertise in every supporting function. Developing each of these blocks internally would require significant time, capital, and specialized talent. Doing so could delay market entry beyond the startupโs viability. Even large semiconductor companies face similar constraints. Advanced-node development demands intense focus. Allocating a team to redesign a standard interface block that has already been implemented elsewhere may be difficult to justify when differentiation lies at the system level, such as an inference chipโs ability to speed up neural network computations. The time it takes to move a new chip from conception to market and risk mitigation, not self-sufficiency, govern most decisions about in-house development versus outsourcing. The economics of advanced IC manufacturing reinforce this reality. When the development cost of a leading-edge chip reaches hundreds of millions of dollars, minimizing risk becomes a central design imperative. In this context, silicon IP emerged as a practical solution. Similar to how software developers rely on preexisting libraries rather than writing every function from scratch, ASIC designers license predesigned, preverified silicon blocksโsuch as processor cores, memory interfaces, and security enginesโfrom highly specialized IP vendors. These blocks can then be integrated into larger, increasingly complex systems. Design scope, verification, and time horizons With the use of silicon IP, industry is able to widen the scope of its designs. Academic efforts tend to focus on block-level innovation: a new analog-to-digital converter architecture or an ultralow-noise amplifier, for instance. These designs typically abstract away many of the complexities of bringing a chip to market, such as packaging constraints, long-term reliability, and manufacturing yield. In industry, the focus shifts to system-level integration. Modern systems on chips, or SoCs, incorporate dozens or even hundreds of functional blocks. Managing signal integrity, timing, firmware interaction, and system-level validation becomes as critical as the design of any individual block. Verification philosophy also diverges sharply. In academia, the goal of verification is to demonstrate that the concept works under nominal conditions, which may not always reflect how it would perform in real applications. Even if only a fraction of fabricated chips from a multiproject wafer operates correctly, the design may still be considered a success if it validates the underlying idea. At my academic lab for instance, we used to receive 40 chips from a TSMC prototyping service and started testing them in batches of five. If the first five or 10 chips proved functional, we had already collected more than enough data for a publication. If some of them failed, we werenโt required to mention this when publishing the results. In industry, verification is exhaustive, critical, and often dominates the development schedule. Failures are measured in parts per million, and even rare anomalies are carefully analyzed and documented to identify root causes and prevent recurrence. When I started at Silicon Creations, I was surprised by the level of detail and scrutiny designs face. Differences in time horizons and economic constraints reinforce each of these contrasts. Academic projects operate on flexible timelines aligned with research and funding cycles. If I missed a deadline, I just had to wait for the next cycle. Industry projects are driven by fixed product schedules and market windows, frequently targeting costly leading-edge nodes to achieve competitive performance, power, and area efficiency. Missing a deadline can negate the value of an entire design and may have major financial consequences along the entire supply chain. In essence, academia explores the design space, asking what is possible, while industry exploits it, determining what is viable at scale. Both are indispensable, but they operate under fundamentally different definitions of success. As ASIC complexity continues to grow, understanding both perspectives will be essential for the next generation of engineers navigating the evolving semiconductor landscape. This article appears in the June 2026 print issue.